Update version to v1.4.222 and commit

OpenAI Plugin Migrates to New Responses API

.github/workflows/release.yml

@@ -111,7 +111,11 @@ jobs:
         env:
           GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run: |
-          gh release view ${{ env.latest_tag }} || gh release create ${{ env.latest_tag }} --title "Release ${{ env.latest_tag }}" --notes "Automated release for ${{ env.latest_tag }}"
+          if ! gh release view ${{ env.latest_tag }} >/dev/null 2>&1; then
+            gh release create ${{ env.latest_tag }} --title "Release ${{ env.latest_tag }}" --notes "Automated release for ${{ env.latest_tag }}"
+          else
+            echo "Release ${{ env.latest_tag }} already exists."
+          fi
 
       - name: Upload release artifact
         if: matrix.os == 'windows-latest'

.github/workflows/update-version-and-create-tag.yml

@@ -11,6 +11,10 @@ on:
 permissions:
   contents: write  # Ensure the workflow has write permissions
 
+concurrency:
+  group: version-update
+  cancel-in-progress: false
+
 jobs:
   update-version:
     if: github.event_name == 'push' && github.ref == 'refs/heads/main'
@@ -30,6 +34,11 @@ jobs:
           git config user.name "github-actions[bot]"
           git config user.email "github-actions[bot]@users.noreply.github.com"
 
+      - name: Pull latest main and tags
+        run: |
+          git pull --rebase origin main
+          git fetch --tags
+
       - name: Get the latest tag
         id: get_latest_tag
         run: |

.gitignore

@@ -58,6 +58,7 @@ coverage.xml
 .hypothesis/
 .pytest_cache/
 cover/
+coverage.out
 
 # Translations
 *.mo

Alma.md

@@ -1,318 +0,0 @@
-# SPQA Policy and State for Alma Security
-
-## Document Purpose
-
-This document captures the SPQA policy and State for Alma Security, a security startup out of Redwood City, Ca.
-
-This is part of the SPQA context that will be used to answer questions and create artifacts for the company, e.g., company strategy, security strategy, quarterly security reports (QSRs), project plans, recommendations on which projects to undertake, which investments to take and avoid, and other such decisions.
-
-A major aspect of the SPQA system is the definition of the company's mission, goals, KPIs, and challenges. These shape everything within the company and thus should be used to shape the recommendations made when asked.
-
-In addition to the clearly stated goals and other defining characteristics listed above, there will also be a streaming list of updates coming into this system using the Activity document.
-
-Those will be changes, updates, or modifications to the direction of the company. For example, if Goal number 4 is to build a new datacenter in Boise, Idaho, but we see an update in the Activity section that says we've lost the ability to build in Boise, we should consider goal #4 out of the picture for prioritization and other decision purposes. In other words, the streaming activity log into this document should be considered updates to the core content.
-
-## Company History
-
-Alma Security was started by Chris Meyers, who was previously at Sigma Systems as CTO and HPE as a senior security engineer.
-
-He started the company because, "I saw a gap in the authentication market, where companies were only looking at one or two aspects of one's identity to do authentication. They we're looking at the whole picture and turning that into a continuous authentication story."
-
-## Company Mission
-
-The mission of Alma Security is to ensure businesses can continuously authenticate their users using their whole selves.
-
-## Company Goals (G1 means goal 1, G2 is goal 2, etc. Treat each item (goal/kpi/etc) as half as important as the one before it.)
-
-NOTE: Some goals are things like project rollout which serve the higher goals. In that case they shouldn't always be considered so much lower priority because one is serving the other.
-
-## Company Goals
-
-- G1: Achieve 20% market share by January 2025
-- G2: Hit 10000 active customers by January 2025
-- G3: Hit a customer trust score of 90+% by January 2025
-- G4: Get churn below 5% by August 2024
-- G5: Launch in Europe by August 2024
-- G6: Launch in India by November 2024
-- G7: Launch Mood-monitor integration by February 2024
-- G8: Launch partnership with Apple Passkeys by June 2024
-
-## Company KPIs
-
-- K1: Current market share percentage
-- K2: Number of active customers
-- K3: Current churn percentage
-- K4: Launched_in_Europe (yes/no)
-- K4: Launched_in_India (yes/no)
-
------------------------------------------------------------------------------------------------------------------------
-
-## Security Team Mission
-
-- SM1: Protect Alma Security's customers and intellectual property from security and privacy incidents.
-
-## Security Team Goals
-
-- SG1: Secure all customer data -- especially biometric -- from security and privacy incidents.
-- SG2: Protect Alma Security's intellectual property from being captured by unauthorized parties.
-- SG3: Reach a time to detect malicious behavior of less than 4 minutes by January 2025
-- SG4: Ensure the public trusts our product, because it's an authentication product we can't survive if people don't trust us.
-- SG5: Reach a time to remediate critical vulnerabilities on crown jewel systems of less than 16 hours by August 2025
-- SG6: Reach a time to remediate critical vulnerabilities on all systems of less than 3 days by August 2025
-- SG5: Reach a time to remediate critical vulnerabilities on crown jewel systems of less than 16 hours by August 2025
-- SG6: Reach a time to remediate critical vulnerabilities on all systems of less than 3 days by August 2025
-- SG7: Complete audit of Apple Passkey integration by February 2025
-- SG8: Complete remediation of Apple Passkey vulnerabilities by February 2025
-
-## Security Team KPIs (How we measure the team)
-
-- SK1: TTD: Time to detect malicious behavior (Minutes)
-- SK1: TTI: Time to begin investigation of malicious behavior (Minutes)
-- SK3: TTR-CJC: Time to remediate critical vulnerabilities on crown jewel systems (Hours)
-- SK3: TTR-C: Time to remediate critical vulnerabilities on all systems (Hours)
-- SK4: PT: Public trust score (Complete, Significant, Moderate, Minimal, Distrust, N/A)
-
-## Risk Register (The things we're most worried about)
-
-- R1: Our infrastructure security team is understaffed by 50% after 5 key people left
-- R2: We are not currently monitoring our external perimeter for attack surface related vulnerabilities like open ports, listening applications, unknown hosts, unknown subdomains pointing to these things, etc. We only do scans once every couple of months and we don't really have anyone to look at the results
-- R3: It takes us multiple days to investigate potential malicious behavior on our systems.
-- R4: We lack a full list of our assets, including externally facing hosts, S3 buckets, etc., which make up our attack surface
-- R5: We have a low public trust score due to the events of 2022.
-
-## Security Team Narrative
-
-### Background
-
-Alma hired a new security team starting in January of 2023 and we have been building out the program since then. The philosophy and approach for the security team is to explicitly articulate what we believe the highest risks are to Alma, to deploy targeted strategies to address those risks, and to use clear, transparent KPIs to show progress towards our goals over time.
-
-### Current Risks
-
-So our risk register looks like this:
-
-1. We are understaffed by 50% after 5 key people left in 2022
-2. Our perimeter is not being monitored for attack surface related vulnerabilities
-3. It takes us too long to detect and start investigating malicious behavior on our systems
-4. We do not have a full list of our assets, which makes it difficult to know what we need to protect
-5. We have a low public trust score due to the events of 2022
-
-### Strategies
-
-As such, our strategies are as follows:
-
-1. Hire 5 more A-tier security professionals
-2. Purchase and implement an attack surface management solution
-3. Invest in our detection and response capabilities
-4. Purchase an asset inventory system that integrates with our attack surface management tool
-5. Leverage PR to share as much of our progress as possible with the public to rebuild trust
-
-### How We're Doing
-
-We believe being transparent about our progress is key to everything, and for that reason we maintain a limited number of KPIs that we update every quarter. These metrics will not change often. They will remain consistent so that it's easy to track how we're spending our resources and the progress we're making.
-
-Those KPIs are:
-
-1. Time to detect malicious behavior
-2. Time to start investigating malicious behavior
-3. Time to remediate critical vulnerabilities on crown jewel systems
-4. Time to remediate critical vulnerabilities on all systems
-5. Our public trust score
-
-As of $DATE$, our KPIs for these are currently:
-
-$GIVE CURRENT KPIs from the Activity section below$
-
-$INSERT GRAPHS OF KPI PROGRESS OVER TIME HERE$
-
-## Security Team Strategies
-
-- STS1: Hire 5 more A-tier security professionals
-- STS2: Purchase an attack surface management solution
-- STS3: Invest in our detection and response capabilities
-- STS4: Purchase an asset inventory system that integrates with our attack surface management tool
-
-## Infrastructure Notes (a basic description of our tech stack and various context around it)
-
-- We currently have no WAF protecting our main web app but we're considering adding one
-- We have had some issues with S3 buckets becoming public, or being set up as public, which has lead to some close calls with customer data almost being exposed.
-- alma.amazon-domain.com is our primary S3 bucket that contains everything, but it's not public readable or listable
-- We have a root account for our AWS account that doesn't yet have 2FA on it, but we're working on fixing that within a few weeks (but it's been open for a few months)
-- We also use Postgres for all our databases.
-- Developers have root access to the all kubernetes nodes via SSH on port 45,001 using a shared developer key issued during laptop provisioning.
-- We're a kubernetes shop and do everything through AWS
-- We're logging most stuff to Cloudtrail and we kind of use Amazon Guarduty, but we don't have a 24/7 team to monitor alerts and logs. We should add that to our list of challenges next time we update our overall policy
-- We also have a Windows infrastructure because some key personnel came from Microsoft. The DC is hosted in our head office which is in Redwood City, and anyone who works in that office (most of the 300 employees) uses that to log in when they start work. The domain is ALMA.
-- There's a domain-joined fileserver running Windows 2012 that most people use to upload new ideas and plans for new products. It uses Windows authentication from the domain.
-- We use a Palo Alto Networks firewall with 2fa using windows authenticator tied to SSO.
-- The name of the AI system doing all this context creation using SPQA is Alma, which is also the name of the company.
-- We use Workday for HR stuff. Slack for realtime communications. Outlook 365 as a service. Sentinel One on the workstations and laptops. Servers in AWS are mostly Amazon Linux 2 with a few Ubuntu boxes that are a few years old.
-- We also primarily use Postgres for all of our systems.
-
-## Team
-
-TEAM MEMBER | TEAM ASSIGNED | SKILLS | PAY LEVEL | LOCATION | PROJECTS
-
-Nadia Khan | Detection and Response | D&R (Expert), AWS (Strong), Python (Expert), Kubernetes (Basic), Postgres (Basic) | $249K | Redwood City
-Chris Magann | Vulnerability Management | VM (Expert), AWS (Strong), Python (Basic), Postgres (Basic) | $212K | Redwood City
-Tigan Wang | Vulnerability Management | VM (Expert), AWS (Strong), Python (Basic), Postgres (Basic) | $217K | Redwood City
-
-## Projects
-
-PROJECT NAME | PROJECT DESCRIPTION | PROJECT PRIORITY | PROJECT MEMBERS | START DATE | END DATE | STATUS | PROJECT COST
-
-WAF Install | Install a WAF in front of our main web app | Critical | Nadia Khan | 2024-01-01 - Ongoing | In Progress | $112K one-time, $9K/month
-
-Multi-Factor Authentication (MFA) Rollout | Implement MFA across all internal and external systems | Critical | Chris Magann | 2024-01-15 | 2024-05-01 | Planned | $80K one-time, $5K/month
-
-Procure and Implement ASM | Implement continuous monitoring for attack surface vulnerabilities | High | Tigan Wang | 2024-02-15 | 2024-06-15 | Not Started | $75K one-time, $6K/month
-
-Data Encryption Upgrade | Upgrade encryption protocols for all sensitive data | Medium | Nadia Khan | 2024-04-01 | 2024-08-01 | Planned | $95K one-time
-
-Incident Response Enhancement | Develop and implement a 24/7 incident response team | High | Nadia Khan | 2024-03-01 | 2024-07-01 | In Progress | $150K one-time, $10K/month
-
-Cloud Security Optimization | Optimize AWS cloud security configurations and practices | Medium | Tigan Wang | 2024-02-01 | 2024-06-01 | In Progress | $100K one-time, $8K/month
-
-S3 Bucket Security | Review and secure all S3 buckets to prevent data breaches | High | Chris Magann | 2024-01-10 | 2024-04-10 | In Progress | $70K one-time, $5K/month
-
-SQL Injection Mitigation | Implement measures to eliminate SQL injection vulnerabilities | High | Tigan Wang | 2024-01-20 | 2024-05-20 | Not Started | $60K one-time
-
-## SECURITY POSTURE (To be referenced for compliance questions and security questionnaires)
-
-July 2019
-Admin accounts still not required to use 2FA.
-Company laptops distributed to employees, no MDM yet for device management.
-AWS IAM roles created for engineers, but root access still frequently used.
-Started basic vulnerability scanning using open-source tools.
-December 2019
-
-MFA enforced for all Google Workspace accounts after a phishing attempt.
-Introduced ClamAV for basic endpoint protection on corporate laptops.
-AWS GuardDuty enabled for threat detection, but no formal incident response team.
-First incident response plan table-top exercise conducted, but findings not fully documented.
-April 2020
-
-Migrated from Google Workspace to Office 365, with MFA enabled for all users.
-Rolled out SentinelOne for endpoint protection on 50% of company laptops.
-Implemented least-privilege access control for AWS IAM roles.
-First formal vendor risk management review completed for major SaaS providers.
-August 2020
-
-Completed full deployment of SentinelOne across all endpoints.
-Implemented AWS CloudWatch for real-time alerts; however, logs still not monitored 24/7.
-Began encrypting all AWS S3 buckets at rest using server-side encryption.
-First internal review of data retention policies, started drafting data disposal policy.
-January 2021
-
-Rolled out Jamf MDM for centralized management of macOS devices, enforcing encryption (FileVault) on all laptops.
-Strengthened Office 365 security by implementing phishing-resistant MFA using authenticator apps.
-AWS KMS introduced for managing encryption keys; manual key rotation policy documented.
-Introduced formal onboarding and offboarding processes for employee account management.
-July 2021
-
-Conditional access policies introduced for Office 365, restricting access based on geography (US-only).
-Conducted company-wide security awareness training for the first time, focusing on phishing threats.
-Completed first backup and disaster recovery (DR) drill with AWS, documenting recovery times.
-AWS Config deployed to monitor and enforce encryption and access control policies across accounts.
-December 2021
-
-Full migration to AWS for all production systems completed.
-Incident response playbook finalized and shared with the security team; still no 24/7 monitoring.
-Documented data classification policies for handling sensitive customer data in preparation for SOC 2 audit.
-First third-party penetration test conducted, critical vulnerabilities identified and remediated within 30 days.
-March 2022
-
-Rolled out company-wide 2FA for all critical systems, including Office 365, AWS, GitHub, and Slack.
-Introduced AWS Secrets Manager for managing sensitive credentials, eliminating hardcoded API keys.
-Updated all documentation for identity and access management in preparation for SOC 2 Type 1 audit.
-First external vulnerability scan completed using Qualys, with remediation SLAs established.
-April 2022
-
-Updated and consolidated all security policies (incident response, access control, data retention) in preparation for SOC 2 audit.
-Conducted tabletop exercise for ransomware response, documenting gaps in the incident response process.
-Implemented Just-In-Time (JIT) access for administrative privileges in AWS, reducing unnecessary persistent access.
-October 2022
-
-Passed SOC 2 Type 1 audit, with recommendations to improve monitoring and asset management.
-Launched quarterly phishing simulations to raise employee awareness and track training effectiveness.
-Fully enforced encryption for all customer data in transit and at rest using AWS KMS.
-Extended GuardDuty to cover all AWS regions; started monitoring alerts daily.
-January 2023
-
-Hired a dedicated CISO and expanded security team by 30%.
-Integrated continuous vulnerability scanning across all externally facing assets using Qualys.
-Conducted first third-party vendor risk assessment to ensure alignment with SOC 2 and internal security standards.
-Implemented automated patch management for all AWS EC2 instances, reducing time to deploy critical patches.
-July 2023
-
-Rolled out continuous attack surface monitoring (ASM) to identify and remediate external vulnerabilities.
-Performed annual data retention review, ensuring compliance with SOC 2 and GDPR requirements.
-Conducted a disaster recovery drill for AWS workloads, achieving a recovery time objective (RTO) of under 4 hours.
-Completed SOC 2 Type 2 readiness assessment, with focus on improving incident response times.
-November 2023
-
-Updated incident response documentation and assigned 24/7 monitoring to a third-party SOC provider.
-Rolled out zero-trust network architecture across the organization, removing reliance on VPN for remote access.
-Passed SOC 2 Type 2 audit with no major findings; recommendations included improved asset inventory tracking.
-Conducted full audit of access control policies and JIT access implementation in preparation for ISO 27001 certification.
-April 2024
-
-Implemented AI-driven threat detection to reduce time to detect security incidents from 10 hours to under 2 hours.
-Completed full encryption audit across all databases, ensuring compliance with GDPR, HIPAA, and other privacy regulations.
-Updated employee training programs to include privacy regulations (GDPR, CCPA) and data handling best practices.
-Completed internal review and audit of vendor access to critical systems as part of SOC 2 compliance effort.
-Completed move of all AWS services to us-west-2  and us-east-1 regions for 100% us-based cloud services.
-October 2024
-
-Conducted organization-wide review of data retention and disposal policies, implementing automated data deletion for expired data.
-Implemented continuous compliance monitoring for SOC 2, with automated alerts for deviations in access controls and encryption settings.
-Finalized implementation of AI-based monitoring and response systems, significantly reducing time to remediate critical vulnerabilities.
-Passed SOC 2 Type 2 and ISO 27001 audits with zero non-conformities, achieving full compliance across all control areas.March 2018
-
-Personal Gmail accounts used for internal and external communication.
-No 2FA enabled on any accounts.
-AWS accounts shared with engineers, no IAM roles or formal access control policies.
-No centralized endpoint protection; employees use personal laptops with no security controls.
-No documented security policies or incident response plan.
-September 2018
-
-Initiated migration from personal Gmail to Google Workspace (G Suite) for business email.
-Password complexity requirements introduced (minimum 8 characters).
-AWS root credentials still shared among team members, no MFA enabled.
-No formal logging or monitoring in place for AWS activity.
-February 2019
-
-Completed migration to Google Workspace; no email encryption yet.
-Introduced a basic password manager (LastPass) but no enforcement policy.
-AWS CloudTrail enabled for logging, but no one is reviewing logs.
-First draft of the incident response plan created, but not tested.
-June 2019
-
-Enforced MFA for Google Workspace admin accounts; standard user
-
-## CURRENT STATE (KPIs, Metrics, Project Activity Updates, etc.)
-
-- October 2022: Current time to detect malicious behavior is 81 hours
-- October 2022: Current time to start investigating malicious behavior is 82 hours
-- October 2022: Current time to remediate critical vulnerabilities on crown jewel systems is 21 days
-- October 2022: Current time to remediate critical vulnerabilities on all systems is 51 days
-- January 2023: Current time to detect malicious behavior is 62 hours
-- January 2023: Current time to start investigating malicious behavior is 72 hours
-- January 2023: Current time to remediate critical vulnerabilities on crown jewel systems is 17 days
-- January 2023: Current time to remediate critical vulnerabilities on all systems is 43 days
-- July 2023: Current time to detect malicious behavior is 29 hours
-- July 2023: Current time to start investigating malicious behavior is 41 hours
-- July 2023: Current time to remediate critical vulnerabilities on crown jewel systems is 12 days
-- July 2023: Current time to remediate critical vulnerabilities on all systems is 29 days
-- November 2023: Current time to start detect malicious behavior is 12 hours
-- November 2023: Current time to start investigating malicious behavior is 16 hours
-- November 2023: Current time to remediate critical vulnerabilities on crown jewel systems is 9 days
-- November 2023: Current time to remediate critical vulnerabilities on all systems is 17 days
-- February 2024: Started attack surface management vendor selection process
-- January 2024: Current time to start detect malicious behavior is 9 hours
-- January 2024: Current time to start investigating malicious behavior is 14 hours
-- January 2024: Current time to remediate critical vulnerabilities on crown jewel systems is 8 days
-- January 2024: Current time to remediate critical vulnerabilities on all systems is 12 days
-- March 2024: We're now remediating critical vulnerabilities on crown jewels in less than 6 days
-- April 2024: We're now remediating all critical vulnerabilities within 11 days
-- July 2024: critical vulnerabilities are now being fixed in 9 days
-- On August 5 we got remediation of critical vulnerabilities down to 7 days

NOTES.md

@@ -2,7 +2,7 @@
 
 - The goal is to bring more encapsulation of the models management and simplified configuration management to bring increased flexibility, transparency on the overall flow, and simplicity in adding new model.
 - We need to differentiate:
-  - Vendors: the producer of models (like OpenAI, Azure, Anthropric, Ollama, ..etc) and their associated APIs
+  - Vendors: the producer of models (like OpenAI, Azure, Anthropic, Ollama, ..etc) and their associated APIs
   - Models: the LLM models these vendors are making public
 - Each vendor and operations allowed by the vendor needs to be encapsulated. This includes:
   - The questions needed to setup the model (like the API key, or the URL)

Pattern_Descriptions/README_Pattern_Descriptions_and_Tags_MGT.md

@@ -53,7 +53,7 @@ Pattern descriptions and tags are managed in pattern_descriptions.json:
 
 3. How to update Pattern short descriptions (one sentence). 
 
-You can update your descriptions in pattern_descriptions.json manually or using LLM assistance (prefered approach). 
+You can update your descriptions in pattern_descriptions.json manually or using LLM assistance (preferred approach). 
 
 Tell AI to look for "Description pending" entries in this file and write a short description based on the extract info in the pattern_extracts.json file. You can also ask your LLM to add tags for those newly added patterns, using other patterns tag assignments as example.    
 

Pattern_Descriptions/pattern_descriptions.json

@@ -1634,8 +1634,8 @@
       ]
     },
     {
-      "patternName": "write_essay",
-      "description": "Create essays with thesis statements and arguments.",
+      "patternName": "write_essay_pg",
+      "description": "Create essays with thesis statements and arguments in the style of Paul Graham.",
       "tags": [
         "WRITING",
         "RESEARCH",
@@ -1703,7 +1703,7 @@
     {
       "patternName": "analyze_bill",
       "description": "Analyze a legislative bill and implications.",
-      "tags": [ 
+      "tags": [
         "ANALYSIS",
         "BILL"
       ]
@@ -1711,14 +1711,14 @@
     {
       "patternName": "analyze_bill_short",
       "description": "Consended - Analyze a legislative bill and implications.",
-      "tags": [ 
+      "tags": [
         "ANALYSIS",
         "BILL"
       ]
     },
     {
       "patternName": "create_coding_feature",
-      "description": "[Description pending]",
+      "description": "Generate secure and composable code features using latest technology and best practices.",
       "tags": [
         "DEVELOPMENT"
       ]
@@ -1774,6 +1774,47 @@
       "tags": [
         "SUMMARIZE"
       ]
+    },
+    {
+      "patternName": "analyze_paper_simple",
+      "description": "Analyze research papers to determine primary findings and assess scientific rigor.",
+      "tags": [
+        "ANALYSIS",
+        "RESEARCH",
+        "WRITING"
+      ]
+    },
+    {
+      "patternName": "analyze_terraform_plan",
+      "description": "Analyze Terraform plans for infrastructure changes, security risks, and cost implications.",
+      "tags": [
+        "ANALYSIS",
+        "DEVOPS"
+      ]
+    },
+    {
+      "patternName": "create_mnemonic_phrases",
+      "description": "Create memorable mnemonic sentences using given words in exact order for memory aids.",
+      "tags": [
+        "CREATIVITY",
+        "LEARNING"
+      ]
+    },
+    {
+      "patternName": "summarize_board_meeting",
+      "description": "Convert board meeting transcripts into formal meeting notes for corporate records.",
+      "tags": [
+        "ANALYSIS",
+        "BUSINESS"
+      ]
+    },
+    {
+      "patternName": "write_essay",
+      "description": "Write essays on given topics in the distinctive style of specified authors.",
+      "tags": [
+        "WRITING",
+        "CREATIVITY"
+      ]
     }
   ]
-}
+}

README.md

@@ -12,16 +12,19 @@ Fabric is graciously supported by…
 ![GitHub top language](https://img.shields.io/github/languages/top/danielmiessler/fabric)
 ![GitHub last commit](https://img.shields.io/github/last-commit/danielmiessler/fabric)
 [![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/danielmiessler/fabric)
 
+<div align="center">
 <p class="align center">
 <h4><code>fabric</code> is an open-source framework for augmenting humans using AI.</h4>
 </p>
+</div>
 
 [Updates](#updates) •
 [What and Why](#what-and-why) •
 [Philosophy](#philosophy) •
-[Installation](#Installation) •
-[Usage](#Usage) •
+[Installation](#installation) •
+[Usage](#usage) •
 [Examples](#examples) •
 [Just Use the Patterns](#just-use-the-patterns) •
 [Custom Patterns](#custom-patterns) •
@@ -32,13 +35,36 @@ Fabric is graciously supported by…
 
 </div>
 
+## What and why
+
+Since the start of modern AI in late 2022 we've seen an **_extraordinary_** number of AI applications for accomplishing tasks. There are thousands of websites, chat-bots, mobile apps, and other interfaces for using all the different AI out there.
+
+It's all really exciting and powerful, but _it's not easy to integrate this functionality into our lives._
+
+<p class="align center">
+<h4>In other words, AI doesn't have a capabilities problem—it has an <em>integration</em> problem.</h4>
+</p>
+
+**Fabric was created to address this by creating and organizing the fundamental units of AI—the prompts themselves!**
+
+Fabric organizes prompts by real-world task, allowing people to create, collect, and organize their most important AI solutions in a single place for use in their favorite tools. And if you're command-line focused, you can use Fabric itself as the interface!
+
+## Intro videos
+
+Keep in mind that many of these were recorded when Fabric was Python-based, so remember to use the current [install instructions](#installation) below.
+
+- [Network Chuck](https://www.youtube.com/watch?v=UbDyjIIGaxQ)
+- [David Bombal](https://www.youtube.com/watch?v=vF-MQmVxnCs)
+- [My Own Intro to the Tool](https://www.youtube.com/watch?v=wPEyyigh10g)
+- [More Fabric YouTube Videos](https://www.youtube.com/results?search_query=fabric+ai)
+
 ## Navigation
 
 - [`fabric`](#fabric)
-  - [Navigation](#navigation)
-  - [Updates](#updates)
   - [What and why](#what-and-why)
   - [Intro videos](#intro-videos)
+  - [Navigation](#navigation)
+  - [Updates](#updates)
   - [Philosophy](#philosophy)
     - [Breaking problems into components](#breaking-problems-into-components)
     - [Too many prompts](#too-many-prompts)
@@ -59,6 +85,10 @@ Fabric is graciously supported by…
       - [Save your files in markdown using aliases](#save-your-files-in-markdown-using-aliases)
     - [Migration](#migration)
     - [Upgrading](#upgrading)
+    - [Shell Completions](#shell-completions)
+      - [Zsh Completion](#zsh-completion)
+      - [Bash Completion](#bash-completion)
+      - [Fish Completion](#fish-completion)
   - [Usage](#usage)
   - [Our approach to prompting](#our-approach-to-prompting)
   - [Examples](#examples)
@@ -83,28 +113,21 @@ Fabric is graciously supported by…
 ## Updates
 
 > [!NOTE]
-> April 16, 2025
 >
-> - Fabric now supports Grok (from XAI)! Update and use `-S` to select it as your default if you want, or just use the shortcut `-m grok-3-beta`. Enjoy!
-
-## What and why
-
-Since the start of 2023 and GenAI we've seen a massive number of AI applications for accomplishing tasks. It's powerful, but _it's not easy to integrate this functionality into our lives._
-
-<div align="center">
-<h4>In other words, AI doesn't have a capabilities problem—it has an <em>integration</em> problem.</h4>
-</div>
-
-Fabric was created to address this by enabling everyone to granularly apply AI to everyday challenges.
-
-## Intro videos
-
-Keep in mind that many of these were recorded when Fabric was Python-based, so remember to use the current [install instructions](#installation) below.
-
-- [Network Chuck](https://www.youtube.com/watch?v=UbDyjIIGaxQ)
-- [David Bombal](https://www.youtube.com/watch?v=vF-MQmVxnCs)
-- [My Own Intro to the Tool](https://www.youtube.com/watch?v=wPEyyigh10g)
-- [More Fabric YouTube Videos](https://www.youtube.com/results?search_query=fabric+ai)
+>June 17, 2025
+>
+>- Fabric now supports Perplexity AI. Configure it by using `fabric -S` to add your Perplexity AI API Key,
+>   and then try:
+>
+>   ```bash
+>   fabric -m sonar-pro "What is the latest world news?"
+>   ```
+>
+>June 11, 2025
+>
+>- Fabric's YouTube transcription now needs `yt-dlp` to be installed. Make sure to install the latest
+> version (2025.06.09 as of this note). The YouTube API key is only needed for comments (the `--comments` flag)
+> and metadata extraction (the `--metadata` flag).
 
 ## Philosophy
 
@@ -411,6 +434,48 @@ The great thing about Go is that it's super easy to upgrade. Just run the same c
 go install github.com/danielmiessler/fabric@latest
 ```
 
+### Shell Completions
+
+Fabric provides shell completion scripts for Zsh, Bash, and Fish
+shells, making it easier to use the CLI by providing tab completion
+for commands and options.
+
+#### Zsh Completion
+
+To enable Zsh completion:
+
+```bash
+# Copy the completion file to a directory in your $fpath
+mkdir -p ~/.zsh/completions
+cp completions/_fabric ~/.zsh/completions/
+
+# Add the directory to fpath in your .zshrc before compinit
+echo 'fpath=(~/.zsh/completions $fpath)' >> ~/.zshrc
+echo 'autoload -Uz compinit && compinit' >> ~/.zshrc
+```
+
+#### Bash Completion
+
+To enable Bash completion:
+
+```bash
+# Source the completion script in your .bashrc
+echo 'source /path/to/fabric/completions/fabric.bash' >> ~/.bashrc
+
+# Or copy to the system-wide bash completion directory
+sudo cp completions/fabric.bash /etc/bash_completion.d/
+```
+
+#### Fish Completion
+
+To enable Fish completion:
+
+```bash
+# Copy the completion file to the fish completions directory
+mkdir -p ~/.config/fish/completions
+cp completions/fabric.fish ~/.config/fish/completions/
+```
+
 ## Usage
 
 Once you have it all set up, here's how to use it.
@@ -419,7 +484,7 @@ Once you have it all set up, here's how to use it.
 fabric -h
 ```
 
-```bash
+```plaintext
 
 Usage:
   fabric [OPTIONS]
@@ -469,6 +534,7 @@ Application Options:
       --serve                       Serve the Fabric Rest API
       --serveOllama                 Serve the Fabric Rest API with ollama endpoints
       --address=                    The address to bind the REST API (default: :8080)
+      --api-key=                    API key used to secure server routes
       --config=                     Path to YAML config file
       --version                     Print current version
       --listextensions              List all registered extensions
@@ -477,6 +543,7 @@ Application Options:
       --strategy=                   Choose a strategy from the available strategies
       --liststrategies              List all strategies
       --listvendors                 List all vendors
+      --shell-complete-list         Output raw list without headers/formatting (for shell completion)
 
 Help Options:
   -h, --help                        Show this help message
@@ -695,7 +762,7 @@ The Streamlit UI supports clipboard operations across different platforms:
 
 - **macOS**: Uses `pbcopy` and `pbpaste` (built-in)
 - **Windows**: Uses `pyperclip` library (install with `pip install pyperclip`)
-- **Linux**: Uses `xclip` (install with `sudo apt-get install xclip` or equivalent for your distro)
+- **Linux**: Uses `xclip` (install with `sudo apt-get install xclip` or equivalent for your Linux distribution)
 
 ## Meta
 
@@ -713,15 +780,15 @@ The Streamlit UI supports clipboard operations across different platforms:
 
 ### Primary contributors
 
-<a href="https://github.com/danielmiessler"><img src="https://avatars.githubusercontent.com/u/50654?v=4" title="Daniel Miessler" width="50" height="50"></a>
-<a href="https://github.com/xssdoctor"><img src="https://avatars.githubusercontent.com/u/9218431?v=4" title="Jonathan Dunn" width="50" height="50"></a>
-<a href="https://github.com/sbehrens"><img src="https://avatars.githubusercontent.com/u/688589?v=4" title="Scott Behrens" width="50" height="50"></a>
-<a href="https://github.com/agu3rra"><img src="https://avatars.githubusercontent.com/u/10410523?v=4" title="Andre Guerra" width="50" height="50"></a>
+<a href="https://github.com/danielmiessler"><img src="https://avatars.githubusercontent.com/u/50654?v=4" title="Daniel Miessler" width="50" height="50" alt="Daniel Miessler"></a>
+<a href="https://github.com/xssdoctor"><img src="https://avatars.githubusercontent.com/u/9218431?v=4" title="Jonathan Dunn" width="50" height="50" alt="Jonathan Dunn"></a>
+<a href="https://github.com/sbehrens"><img src="https://avatars.githubusercontent.com/u/688589?v=4" title="Scott Behrens" width="50" height="50" alt="Scott Behrens"></a>
+<a href="https://github.com/agu3rra"><img src="https://avatars.githubusercontent.com/u/10410523?v=4" title="Andre Guerra" width="50" height="50" alt="Andre Guerra"></a>
 
 ### Contributors
 
 <a href="https://github.com/danielmiessler/fabric/graphs/contributors">
-  <img src="https://contrib.rocks/image?repo=danielmiessler/fabric" />
+  <img src="https://contrib.rocks/image?repo=danielmiessler/fabric" alt="contrib.rocks" />
 </a>
 
 Made with [contrib.rocks](https://contrib.rocks).

Web Interface MOD Readme Files/pr-1284-update.md

@@ -1,295 +0,0 @@
-This Cummulative PR adds several Web UI and functionality improvements to make pattern selection more intuitive with the addition of pattern descriptions, ability to save favorite patterns, a Pattern TAG system, powerful multilingual capabilities, PDF-to-markdown functionnalities, a help reference section, more robust Youtube processing and a variety of other ui improvements. 
-
-## 🎥 Demo Video
-https://youtu.be/XMzjgqvdltM
-
-
-
-## 🌟 Key Features
-
-### 1. Web UI and Pattern Selection Improvements
-- Pattern Descriptions
-- Pattern Tags
-- Pattern Favourites
-- Pattern Search bar
-- PDF to markdown (pdf as pattern input)
-- Better handling of Youtube url
-- Multilingual Support
-- Web UI refinements for clearer interaction
-- Help section via modal  
-
-### 2. Multilingual Support System
-- Seamless language switching via UI dropdown 
-- Persistent language state management
-- Pattern processing now use the selected language seamlessly
-
-### 3. YouTube Integration Enhancement
-- Robust language handling for YouTube transcript processing
-- Chunk-based language maintenance for long transcripts
-- Consistent language output throughout transcript analysis
-
-### 4. Enhanced Tag Management Integration
-
-The tag filtering system has been deeply integrated into the Pattern Selection interface through several UI enhancements:
-
-1. **Dual-Position Tag Panel**
-   - Sliding panel positioned to the right of pattern modal
-   - Dynamic toggle button that adapts position and text based on panel state
-   - Smooth transitions for opening/closing animations
-
-2. **Tag Selection Visibility**
-   - New dedicated tag display section in pattern modal
-   - Visual separation through subtle background styling
-   - Immediate feedback showing selected tags with comma separation
-   - Inline reset capability for quick tag clearing
-
-3. **Improved User Experience**
-   - Clear visual hierarchy between pattern list and tag filtering
-   - Multiple ways to manage tags (panel or quick reset)
-   - Consistent styling with existing design language
-   - Space-efficient tag brick layout in 3-column grid
-
-4. **Technical Implementation**
-   - Reactive tag state management
-   - Efficient tag filtering logic
-   - Proper event dispatching between components
-   - Maintained accessibility standards
-   - Responsive design considerations
-
-
-5. **PDF to Markdown conversion functionality for the web interface**
-- Automatic detection and processing of PDF files in chat
-- Conversion to markdown format for LLM processing
-- Installation instructions from the pdf-to-markdown repository
-
-The PDF conversion module has been integrated in the svelte web browser interface. Once installed, it will automatically detect pdf files in the chat interface and convert them to markdown 
-
-
-## HOW TO INSTALL PDF-TO-MARKDOWN
-If you need to update the web component follow the instructions in "Web Interface MOD Readme Files/WEB V2 Install Guide.md".  
-
-Assuming your web install is up to date and web svelte config complete, you can simply follow these steps to add Pdf-to-mardown. 
-
-# FROM FABRIC ROOT DIRECTORY
-  cd .. web
-
-# Install in this sequence: 
-# Step 1
-npm install -D patch-package
-# Step 2
-npm install -D pdfjs-dist@2.5.207
-# Step 3
-npm install -D github:jzillmann/pdf-to-markdown#modularize
-
-These enhancements create a more intuitive and efficient pattern discovery experience, allowing users to quickly filter and find relevant patterns while maintaining a clean, modern interface.
-
-
-## 🛠 Technical Implementation
-
-### Language Support Architecture
-```typescript
-// Language state management
-export const languageStore = writable<string>('');
-
-// Chat input language detection
-if (qualifier === 'fr') {
-  languageStore.set('fr');
-  userInput = userInput.replace(/--fr\s*/, '');
-}
-
-// Service layer integration
-const language = get(languageStore) || 'en';
-const languageInstruction = language !== 'en' 
-  ? `. Please use the language '${language}' for the output.` 
-  : '';
-```
-
-### YouTube Processing Enhancement
-```typescript
-// Process stream with language instruction per chunk
-await chatService.processStream(
-  stream,
-  (content: string, response?: StreamResponse) => {
-    if (currentLanguage !== 'en') {
-      content = `${content}. Please use the language '${currentLanguage}' for the output.`;
-    }
-    // Update messages...
-  }
-);
-```
-# Pattern Descriptions and Tags Management
-
-This document explains the complete workflow for managing pattern descriptions and tags, including how to process new patterns and maintain metadata.
-
-## System Overview
-
-The pattern system follows this hierarchy:
-1. `~/.config/fabric/patterns/` directory: The source of truth for available patterns
-2. `pattern_extracts.json`: Contains first 500 words of each pattern for reference
-3. `pattern_descriptions.json`: Stores pattern metadata (descriptions and tags)
-4. `web/static/data/pattern_descriptions.json`: Web-accessible copy for the interface
-
-## Pattern Processing Workflow
-
-### 1. Adding New Patterns
-- Add patterns to `~/.config/fabric/patterns/`
-- Run extract_patterns.py to process new additions:
-  ```bash
-  python extract_patterns.py
-
-The Python Script automatically:
-- Creates pattern extracts for reference
-- Adds placeholder entries in descriptions file
-- Syncs to web interface
-
-### 2. Pattern Extract Creation
-The script extracts first 500 words from each pattern's system.md file to:
-
-- Provide context for writing descriptions
-- Maintain reference material
-- Aid in pattern categorization
-
-### 3. Description and Tag Management
-Pattern descriptions and tags are managed in pattern_descriptions.json:
-
-
-{
-  "patterns": [
-    {
-      "patternName": "pattern_name",
-      "description": "[Description pending]",
-      "tags": []
-    }
-  ]
-}
-
-
-## Completing Pattern Metadata
-
-### Writing Descriptions
-1. Check pattern_descriptions.json for "[Description pending]" entries
-2. Reference pattern_extracts.json for context
-
-3. How to update Pattern short descriptions (one sentence). 
-
-You can update your descriptions in pattern_descriptions.json manually or using LLM assistance (prefered approach). 
-
-Tell AI to look for "Description pending" entries in this file and write a short description based on the extract info in the pattern_extracts.json file. You can also ask your LLM to add tags for those newly added patterns, using other patterns tag assignments as example.    
-
-### Managing Tags
-1. Add appropriate tags to new patterns
-2. Update existing tags as needed
-3. Tags are stored as arrays: ["TAG1", "TAG2"]
-4. Edit pattern_descriptions.json directly to modify tags
-5. Make tags your own. You can delete, replace, amend existing tags.
-
-## File Synchronization
-
-The script maintains synchronization between:
-- Local pattern_descriptions.json
-- Web interface copy in static/data/
-- No manual file copying needed
-
-## Best Practices
-
-1. Run extract_patterns.py when:
-   - Adding new patterns
-   - Updating existing patterns
-   - Modifying pattern structure
-
-2. Description Writing:
-   - Use pattern extracts for context
-   - Keep descriptions clear and concise
-   - Focus on pattern purpose and usage
-
-3. Tag Management:
-   - Use consistent tag categories
-   - Apply multiple tags when relevant
-   - Update tags to reflect pattern evolution
-
-## Troubleshooting
-
-If patterns are not showing in the web interface:
-1. Verify pattern_descriptions.json format
-2. Check web static copy exists
-3. Ensure proper file permissions
-4. Run extract_patterns.py to resync
-
-## File Structure
-
-fabric/
-├── patterns/                     # Pattern source files
-├── PATTERN_DESCRIPTIONS/
-│   ├── extract_patterns.py      # Pattern processing script
-│   ├── pattern_extracts.json    # Pattern content references
-│   └── pattern_descriptions.json # Pattern metadata
-└── web/
-    └── static/
-        └── data/
-            └── pattern_descriptions.json # Web interface copy
-
-
-
-
-
-## 🎯 Usage Examples
-
-### 1. Using Language Qualifiers
-```
-User: What is the weather?
-AI: The weather information...
-
-User: --fr What is the weather?
-AI: Voici les informations météo...
-```
-
-### 2. Global Settings
-1. Select language from dropdown
-2. All interactions use selected language
-3. Automatic reset to English after each message
-
-### 3. YouTube Analysis
-```
-User: Analyze this YouTube video --fr
-AI: [Provides analysis in French, maintaining language throughout the transcript]
-```
-
-## 💡 Key Benefits
-
-1. **Enhanced User Experience**
-   - Intuitive language switching
-   - Consistent language handling
-   - Seamless integration with existing features
-
-2. **Robust Implementation**
-   - Simple yet powerful design
-   - No complex language detection needed
-   - Direct AI instruction approach
-
-3. **Maintainable Architecture**
-   - Clean separation of concerns
-   - Stateful language management
-   - Easy to extend for new languages
-
-4. **YouTube Integration**
-   - Handles long transcripts effectively
-   - Maintains language consistency
-   - Robust chunk processing
-
-## 🔄 Implementation Notes
-
-1. **State Management**
-   - Language persists until changed
-   - Resets to English after each message
-   - Handles UI state updates efficiently
-
-2. **Error Handling**
-   - Invalid qualifiers are ignored
-   - Unknown languages default to English
-   - Proper store reset on errors
-
-3. **Best Practices**
-   - Clear language instructions
-   - Consistent state management
-   - Robust error handling
-

chat/chat.go

@@ -0,0 +1,132 @@
+package chat
+
+import (
+	"encoding/json"
+	"errors"
+)
+
+const (
+	ChatMessageRoleSystem    = "system"
+	ChatMessageRoleUser      = "user"
+	ChatMessageRoleAssistant = "assistant"
+	ChatMessageRoleFunction  = "function"
+	ChatMessageRoleTool      = "tool"
+	ChatMessageRoleDeveloper = "developer"
+)
+
+var ErrContentFieldsMisused = errors.New("can't use both Content and MultiContent properties simultaneously")
+
+type ChatMessagePartType string
+
+const (
+	ChatMessagePartTypeText     ChatMessagePartType = "text"
+	ChatMessagePartTypeImageURL ChatMessagePartType = "image_url"
+)
+
+type ChatMessageImageURL struct {
+	URL string `json:"url,omitempty"`
+}
+
+type ChatMessagePart struct {
+	Type     ChatMessagePartType  `json:"type,omitempty"`
+	Text     string               `json:"text,omitempty"`
+	ImageURL *ChatMessageImageURL `json:"image_url,omitempty"`
+}
+
+type FunctionCall struct {
+	Name      string `json:"name,omitempty"`
+	Arguments string `json:"arguments,omitempty"`
+}
+
+type ToolType string
+
+const (
+	ToolTypeFunction ToolType = "function"
+)
+
+type ToolCall struct {
+	Index    *int         `json:"index,omitempty"`
+	ID       string       `json:"id,omitempty"`
+	Type     ToolType     `json:"type"`
+	Function FunctionCall `json:"function"`
+}
+
+type ChatCompletionMessage struct {
+	Role             string            `json:"role"`
+	Content          string            `json:"content,omitempty"`
+	Refusal          string            `json:"refusal,omitempty"`
+	MultiContent     []ChatMessagePart `json:"-"`
+	Name             string            `json:"name,omitempty"`
+	ReasoningContent string            `json:"reasoning_content,omitempty"`
+	FunctionCall     *FunctionCall     `json:"function_call,omitempty"`
+	ToolCalls        []ToolCall        `json:"tool_calls,omitempty"`
+	ToolCallID       string            `json:"tool_call_id,omitempty"`
+}
+
+func (m ChatCompletionMessage) MarshalJSON() ([]byte, error) {
+	if m.Content != "" && m.MultiContent != nil {
+		return nil, ErrContentFieldsMisused
+	}
+	if len(m.MultiContent) > 0 {
+		msg := struct {
+			Role             string            `json:"role"`
+			Content          string            `json:"-"`
+			Refusal          string            `json:"refusal,omitempty"`
+			MultiContent     []ChatMessagePart `json:"content,omitempty"`
+			Name             string            `json:"name,omitempty"`
+			ReasoningContent string            `json:"reasoning_content,omitempty"`
+			FunctionCall     *FunctionCall     `json:"function_call,omitempty"`
+			ToolCalls        []ToolCall        `json:"tool_calls,omitempty"`
+			ToolCallID       string            `json:"tool_call_id,omitempty"`
+		}(m)
+		return json.Marshal(msg)
+	}
+
+	msg := struct {
+		Role             string            `json:"role"`
+		Content          string            `json:"content,omitempty"`
+		Refusal          string            `json:"refusal,omitempty"`
+		MultiContent     []ChatMessagePart `json:"-"`
+		Name             string            `json:"name,omitempty"`
+		ReasoningContent string            `json:"reasoning_content,omitempty"`
+		FunctionCall     *FunctionCall     `json:"function_call,omitempty"`
+		ToolCalls        []ToolCall        `json:"tool_calls,omitempty"`
+		ToolCallID       string            `json:"tool_call_id,omitempty"`
+	}(m)
+	return json.Marshal(msg)
+}
+
+func (m *ChatCompletionMessage) UnmarshalJSON(bs []byte) error {
+	msg := struct {
+		Role             string `json:"role"`
+		Content          string `json:"content"`
+		Refusal          string `json:"refusal,omitempty"`
+		MultiContent     []ChatMessagePart
+		Name             string        `json:"name,omitempty"`
+		ReasoningContent string        `json:"reasoning_content,omitempty"`
+		FunctionCall     *FunctionCall `json:"function_call,omitempty"`
+		ToolCalls        []ToolCall    `json:"tool_calls,omitempty"`
+		ToolCallID       string        `json:"tool_call_id,omitempty"`
+	}{}
+
+	if err := json.Unmarshal(bs, &msg); err == nil {
+		*m = ChatCompletionMessage(msg)
+		return nil
+	}
+	multiMsg := struct {
+		Role             string `json:"role"`
+		Content          string
+		Refusal          string            `json:"refusal,omitempty"`
+		MultiContent     []ChatMessagePart `json:"content"`
+		Name             string            `json:"name,omitempty"`
+		ReasoningContent string            `json:"reasoning_content,omitempty"`
+		FunctionCall     *FunctionCall     `json:"function_call,omitempty"`
+		ToolCalls        []ToolCall        `json:"tool_calls,omitempty"`
+		ToolCallID       string            `json:"tool_call_id,omitempty"`
+	}{}
+	if err := json.Unmarshal(bs, &multiMsg); err != nil {
+		return err
+	}
+	*m = ChatCompletionMessage(multiMsg)
+	return nil
+}

cli/cli.go

@@ -93,7 +93,7 @@ func Cli(version string) (err error) {
 	}
 
 	if currentFlags.ListPatterns {
-		err = fabricDb.Patterns.ListNames()
+		err = fabricDb.Patterns.ListNames(currentFlags.ShellCompleteOutput)
 		return
 	}
 
@@ -102,17 +102,17 @@ func Cli(version string) (err error) {
 		if models, err = registry.VendorManager.GetModels(); err != nil {
 			return
 		}
-		models.Print()
+		models.Print(currentFlags.ShellCompleteOutput)
 		return
 	}
 
 	if currentFlags.ListAllContexts {
-		err = fabricDb.Contexts.ListNames()
+		err = fabricDb.Contexts.ListNames(currentFlags.ShellCompleteOutput)
 		return
 	}
 
 	if currentFlags.ListAllSessions {
-		err = fabricDb.Sessions.ListNames()
+		err = fabricDb.Sessions.ListNames(currentFlags.ShellCompleteOutput)
 		return
 	}
 
@@ -160,7 +160,7 @@ func Cli(version string) (err error) {
 	}
 
 	if currentFlags.ListStrategies {
-		err = registry.Strategies.ListStrategies()
+		err = registry.Strategies.ListStrategies(currentFlags.ShellCompleteOutput)
 		return
 	}
 
@@ -256,7 +256,8 @@ func Cli(version string) (err error) {
 	}
 
 	var chatter *core.Chatter
-	if chatter, err = registry.GetChatter(currentFlags.Model, currentFlags.ModelContextLength, currentFlags.Strategy, currentFlags.Stream, currentFlags.DryRun); err != nil {
+	if chatter, err = registry.GetChatter(currentFlags.Model, currentFlags.ModelContextLength,
+		currentFlags.Strategy, currentFlags.Stream, currentFlags.DryRun); err != nil {
 		return
 	}
 

cli/flags.go

@@ -10,9 +10,9 @@ import (
 	"strconv"
 	"strings"
 
+	"github.com/danielmiessler/fabric/chat"
 	"github.com/danielmiessler/fabric/common"
 	"github.com/jessevdk/go-flags"
-	goopenai "github.com/sashabaranov/go-openai"
 	"golang.org/x/text/language"
 	"gopkg.in/yaml.v2"
 )
@@ -73,6 +73,7 @@ type Flags struct {
 	Strategy                        string            `long:"strategy" description:"Choose a strategy from the available strategies" default:""`
 	ListStrategies                  bool              `long:"liststrategies" description:"List all strategies"`
 	ListVendors                     bool              `long:"listvendors" description:"List all vendors"`
+	ShellCompleteOutput             bool              `long:"shell-complete-list" description:"Output raw list without headers/formatting (for shell completion)"`
 }
 
 var debug = false
@@ -277,22 +278,15 @@ func (o *Flags) BuildChatRequest(Meta string) (ret *common.ChatRequest, err erro
 		Meta:             Meta,
 	}
 
-	var message *goopenai.ChatCompletionMessage
-	if len(o.Attachments) == 0 {
-		if o.Message != "" {
-			message = &goopenai.ChatCompletionMessage{
-				Role:    goopenai.ChatMessageRoleUser,
-				Content: strings.TrimSpace(o.Message),
-			}
-		}
-	} else {
-		message = &goopenai.ChatCompletionMessage{
-			Role: goopenai.ChatMessageRoleUser,
+	var message *chat.ChatCompletionMessage
+	if len(o.Attachments) > 0 {
+		message = &chat.ChatCompletionMessage{
+			Role: chat.ChatMessageRoleUser,
 		}
 
 		if o.Message != "" {
-			message.MultiContent = append(message.MultiContent, goopenai.ChatMessagePart{
-				Type: goopenai.ChatMessagePartTypeText,
+			message.MultiContent = append(message.MultiContent, chat.ChatMessagePart{
+				Type: chat.ChatMessagePartTypeText,
 				Text: strings.TrimSpace(o.Message),
 			})
 		}
@@ -315,14 +309,20 @@ func (o *Flags) BuildChatRequest(Meta string) (ret *common.ChatRequest, err erro
 				dataURL := fmt.Sprintf("data:%s;base64,%s", mimeType, base64Image)
 				url = &dataURL
 			}
-			message.MultiContent = append(message.MultiContent, goopenai.ChatMessagePart{
-				Type: goopenai.ChatMessagePartTypeImageURL,
-				ImageURL: &goopenai.ChatMessageImageURL{
+			message.MultiContent = append(message.MultiContent, chat.ChatMessagePart{
+				Type: chat.ChatMessagePartTypeImageURL,
+				ImageURL: &chat.ChatMessageImageURL{
 					URL: *url,
 				},
 			})
 		}
+	} else if o.Message != "" {
+		message = &chat.ChatCompletionMessage{
+			Role:    chat.ChatMessageRoleUser,
+			Content: strings.TrimSpace(o.Message),
+		}
 	}
+
 	ret.Message = message
 
 	if o.Language != "" {

common/domain.go

@@ -1,6 +1,6 @@
 package common
 
-import goopenai "github.com/sashabaranov/go-openai"
+import "github.com/danielmiessler/fabric/chat"
 
 const ChatMessageRoleMeta = "meta"
 
@@ -9,7 +9,7 @@ type ChatRequest struct {
 	SessionName      string
 	PatternName      string
 	PatternVariables map[string]string
-	Message          *goopenai.ChatCompletionMessage
+	Message          *chat.ChatCompletionMessage
 	Language         string
 	Meta             string
 	InputHasVars     bool
@@ -25,10 +25,11 @@ type ChatOptions struct {
 	Raw                bool
 	Seed               int
 	ModelContextLength int
+	MaxTokens          int
 }
 
 // NormalizeMessages remove empty messages and ensure messages order user-assist-user
-func NormalizeMessages(msgs []*goopenai.ChatCompletionMessage, defaultUserMessage string) (ret []*goopenai.ChatCompletionMessage) {
+func NormalizeMessages(msgs []*chat.ChatCompletionMessage, defaultUserMessage string) (ret []*chat.ChatCompletionMessage) {
 	// Iterate over messages to enforce the odd position rule for user messages
 	fullMessageIndex := 0
 	for _, message := range msgs {
@@ -38,8 +39,8 @@ func NormalizeMessages(msgs []*goopenai.ChatCompletionMessage, defaultUserMessag
 		}
 
 		// Ensure, that each odd position shall be a user message
-		if fullMessageIndex%2 == 0 && message.Role != goopenai.ChatMessageRoleUser {
-			ret = append(ret, &goopenai.ChatCompletionMessage{Role: goopenai.ChatMessageRoleUser, Content: defaultUserMessage})
+		if fullMessageIndex%2 == 0 && message.Role != chat.ChatMessageRoleUser {
+			ret = append(ret, &chat.ChatCompletionMessage{Role: chat.ChatMessageRoleUser, Content: defaultUserMessage})
 			fullMessageIndex++
 		}
 		ret = append(ret, message)

common/domain_test.go

@@ -3,23 +3,23 @@ package common
 import (
 	"testing"
 
-	goopenai "github.com/sashabaranov/go-openai"
+	"github.com/danielmiessler/fabric/chat"
 	"github.com/stretchr/testify/assert"
 )
 
 func TestNormalizeMessages(t *testing.T) {
-	msgs := []*goopenai.ChatCompletionMessage{
-		{Role: goopenai.ChatMessageRoleUser, Content: "Hello"},
-		{Role: goopenai.ChatMessageRoleAssistant, Content: "Hi there!"},
-		{Role: goopenai.ChatMessageRoleUser, Content: ""},
-		{Role: goopenai.ChatMessageRoleUser, Content: ""},
-		{Role: goopenai.ChatMessageRoleUser, Content: "How are you?"},
+	msgs := []*chat.ChatCompletionMessage{
+		{Role: chat.ChatMessageRoleUser, Content: "Hello"},
+		{Role: chat.ChatMessageRoleAssistant, Content: "Hi there!"},
+		{Role: chat.ChatMessageRoleUser, Content: ""},
+		{Role: chat.ChatMessageRoleUser, Content: ""},
+		{Role: chat.ChatMessageRoleUser, Content: "How are you?"},
 	}
 
-	expected := []*goopenai.ChatCompletionMessage{
-		{Role: goopenai.ChatMessageRoleUser, Content: "Hello"},
-		{Role: goopenai.ChatMessageRoleAssistant, Content: "Hi there!"},
-		{Role: goopenai.ChatMessageRoleUser, Content: "How are you?"},
+	expected := []*chat.ChatCompletionMessage{
+		{Role: chat.ChatMessageRoleUser, Content: "Hello"},
+		{Role: chat.ChatMessageRoleAssistant, Content: "Hi there!"},
+		{Role: chat.ChatMessageRoleUser, Content: "How are you?"},
 	}
 
 	actual := NormalizeMessages(msgs, "default")

common/groups_items.go

@@ -42,13 +42,43 @@ func (o *GroupsItemsSelector[I]) AddGroupItems(group string, items ...I) {
 	o.GroupsItems = append(o.GroupsItems, &GroupItems[I]{group, items})
 }
 
+// getSortedGroupsItems returns a new slice of GroupItems with both groups and their items
+// sorted alphabetically in a case-insensitive manner. The original GroupsItems are not modified.
+func (o *GroupsItemsSelector[I]) getSortedGroupsItems() []*GroupItems[I] {
+	// Copy and sort groups (case‑insensitive)
+	sortedGroupsItems := make([]*GroupItems[I], len(o.GroupsItems))
+	copy(sortedGroupsItems, o.GroupsItems)
+	sort.SliceStable(sortedGroupsItems, func(i, j int) bool {
+		return strings.ToLower(sortedGroupsItems[i].Group) < strings.ToLower(sortedGroupsItems[j].Group)
+	})
+
+	// For each group, sort its items
+	for i, groupItems := range sortedGroupsItems {
+		sortedItems := make([]I, len(groupItems.Items))
+		copy(sortedItems, groupItems.Items)
+		sort.SliceStable(sortedItems, func(i, j int) bool {
+			return strings.ToLower(o.GetItemKey(sortedItems[i])) < strings.ToLower(o.GetItemKey(sortedItems[j]))
+		})
+
+		// Create a new GroupItems with the sorted items
+		sortedGroupsItems[i] = &GroupItems[I]{
+			Group: groupItems.Group,
+			Items: sortedItems,
+		}
+	}
+
+	return sortedGroupsItems
+}
+
 func (o *GroupsItemsSelector[I]) GetGroupAndItemByItemNumber(number int) (group string, item I, err error) {
 	var currentItemNumber int
 	found := false
 
-	for _, groupItems := range o.GroupsItems {
-		if currentItemNumber+groupItems.Count() < number {
-			currentItemNumber += groupItems.Count()
+	sortedGroupsItems := o.getSortedGroupsItems()
+
+	for _, groupItems := range sortedGroupsItems {
+		if currentItemNumber+len(groupItems.Items) < number {
+			currentItemNumber += len(groupItems.Items)
 			continue
 		}
 
@@ -61,6 +91,10 @@ func (o *GroupsItemsSelector[I]) GetGroupAndItemByItemNumber(number int) (group
 				break
 			}
 		}
+
+		if found {
+			break
+		}
 	}
 
 	if !found {
@@ -69,35 +103,30 @@ func (o *GroupsItemsSelector[I]) GetGroupAndItemByItemNumber(number int) (group
 	return
 }
 
-func (o *GroupsItemsSelector[I]) Print() {
-	fmt.Printf("\n%v:\n", o.SelectionLabel)
+func (o *GroupsItemsSelector[I]) Print(shellCompleteList bool) {
+	// Only print the section header if not in plain output mode
+	if !shellCompleteList {
+		fmt.Printf("\n%v:\n", o.SelectionLabel)
+	}
 
 	var currentItemIndex int
-	// Create a copy of groups to sort
-	sortedGroupsItems := make([]*GroupItems[I], len(o.GroupsItems))
-	copy(sortedGroupsItems, o.GroupsItems)
-
-	// Sort groups alphabetically case-insensitive
-	sort.SliceStable(sortedGroupsItems, func(i, j int) bool {
-		return strings.ToLower(sortedGroupsItems[i].Group) < strings.ToLower(sortedGroupsItems[j].Group)
-	})
+	sortedGroupsItems := o.getSortedGroupsItems()
 
 	for _, groupItems := range sortedGroupsItems {
-		fmt.Println()
-		fmt.Printf("%s\n", groupItems.Group)
-		fmt.Println()
+		if !shellCompleteList {
+			fmt.Println()
+			fmt.Printf("%s\n\n", groupItems.Group)
+		}
 
-		// Create a copy of items to sort
-		sortedItems := make([]I, len(groupItems.Items))
-		copy(sortedItems, groupItems.Items)
-		// Sort items alphabetically case-insensitive
-		sort.SliceStable(sortedItems, func(i, j int) bool {
-			return strings.ToLower(o.GetItemKey(sortedItems[i])) < strings.ToLower(o.GetItemKey(sortedItems[j]))
-		})
-
-		for _, item := range sortedItems {
+		for _, item := range groupItems.Items {
 			currentItemIndex++
-			fmt.Printf("\t[%d]\t%s\n", currentItemIndex, o.GetItemKey(item))
+			if shellCompleteList {
+				// plain mode: "index key"
+				fmt.Printf("%s\n", o.GetItemKey(item))
+			} else {
+				// formatted mode: "[index]    key"
+				fmt.Printf("\t[%d]\t%s\n", currentItemIndex, o.GetItemKey(item))
+			}
 		}
 	}
 }

completion/fabric.fish

@@ -1,158 +0,0 @@
-function __fabric_models
-    # Get models from fabric --listmodels
-    fabric --listmodels 2>/dev/null | grep '\\[' | cut -f 3
-end
-
-function __fabric_patterns
-    # Get patterns from fabric --listpatterns
-    fabric --listpatterns 2>/dev/null
-end
-
-function __fabric_contexts
-    # Get contexts from fabric --listcontexts
-    fabric --listcontexts 2>/dev/null | grep -v 'No Contexts'
-end
-
-function __fabric_sessions
-    # Get sessions from fabric --listsessions
-    fabric --listsessions 2>/dev/null
-end
-
-function __fabric_strategies
-    # Get strategies from fabric --liststrategies, add descriptions
-    fabric --liststrategies 2>/dev/null | tail -n +2 | sed 's/ \+/\t/' 
-end
-
-function __fabric_extensions
-    # Get extensions from fabric --listextensions
-    fabric --listextensions 2>/dev/null
-end
-
-# Main fabric command
-complete -c fabric -f
-
-# Pattern selection
-complete -c fabric -s p -l pattern -x -a "(__fabric_patterns)" -d "Choose a pattern from the available patterns"
-
-# Variables for patterns
-complete -c fabric -s v -l variable -x -d "Values for pattern variables, e.g. -v=#role:expert -v=#points:30"
-
-# Context selection
-complete -c fabric -s C -l context -x -a "(__fabric_contexts)" -d "Choose a context from the available contexts"
-
-# Session selection
-complete -c fabric -l session -x -a "(__fabric_sessions)" -d "Choose a session from the available sessions"
-
-# Attachments
-complete -c fabric -s a -l attachment -r -d "Attachment path or URL (e.g. for OpenAI image recognition messages)"
-
-# Setup
-complete -c fabric -s S -l setup -d "Run setup for all reconfigurable parts of fabric"
-
-# Temperature
-complete -c fabric -s t -l temperature -x -d "Set temperature (default: 0.7)"
-
-# Top P
-complete -c fabric -s T -l topp -x -d "Set top P (default: 0.9)"
-
-# Stream output
-complete -c fabric -s s -l stream -d "Stream output"
-
-# Presence penalty
-complete -c fabric -s P -l presencepenalty -x -d "Set presence penalty (default: 0.0)"
-
-# Raw mode
-complete -c fabric -s r -l raw -d "Use the defaults of the model without sending chat options"
-
-# Frequency penalty
-complete -c fabric -s F -l frequencypenalty -x -d "Set frequency penalty (default: 0.0)"
-
-# List patterns
-complete -c fabric -s l -l listpatterns -d "List all patterns"
-
-# List models
-complete -c fabric -s L -l listmodels -d "List all available models"
-
-# List contexts
-complete -c fabric -s x -l listcontexts -d "List all contexts"
-
-# List sessions
-complete -c fabric -s X -l listsessions -d "List all sessions"
-
-# Update patterns
-complete -c fabric -s U -l updatepatterns -d "Update patterns"
-
-# Copy to clipboard
-complete -c fabric -s c -l copy -d "Copy to clipboard"
-
-# Model selection
-complete -c fabric -s m -l model -x -a "(__fabric_models)" -d "Choose model"
-
-# Model context length
-complete -c fabric -l modelContextLength -x -d "Model context length (only affects ollama)"
-
-# Output to file
-complete -c fabric -s o -l output -r -F -d "Output to file"
-
-# Output session
-complete -c fabric -l output-session -d "Output the entire session to the output file"
-
-# Latest patterns
-complete -c fabric -s n -l latest -x -d "Number of latest patterns to list"
-
-# Change default model
-complete -c fabric -s d -l changeDefaultModel -d "Change default model"
-
-# YouTube operations
-complete -c fabric -s y -l youtube -x -d "YouTube video or playlist URL to grab content from"
-complete -c fabric -l playlist -d "Prefer playlist over video if both ids are present in the URL"
-complete -c fabric -l transcript -d "Grab transcript from YouTube video (default)"
-complete -c fabric -l transcript-with-timestamps -d "Grab transcript from YouTube video with timestamps"
-complete -c fabric -l comments -d "Grab comments from YouTube video"
-complete -c fabric -l metadata -d "Output video metadata"
-
-# Language specification
-complete -c fabric -s g -l language -x -d "Specify the Language Code for the chat, e.g. -g=en -g=zh"
-
-# Jina AI operations
-complete -c fabric -s u -l scrape_url -x -d "Scrape website URL to markdown using Jina AI"
-complete -c fabric -s q -l scrape_question -x -d "Search question using Jina AI"
-
-# Seed
-complete -c fabric -s e -l seed -x -d "Seed to be used for LMM generation"
-
-# Context and session operations
-complete -c fabric -s w -l wipecontext -x -a "(__fabric_contexts)" -d "Wipe context"
-complete -c fabric -s W -l wipesession -x -a "(__fabric_sessions)" -d "Wipe session"
-complete -c fabric -l printcontext -x -a "(__fabric_contexts)" -d "Print context"
-complete -c fabric -l printsession -x -a "(__fabric_sessions)" -d "Print session"
-
-# HTML readability
-complete -c fabric -l readability -d "Convert HTML input into a clean, readable view"
-
-# Variables in input
-complete -c fabric -l input-has-vars -d "Apply variables to user input"
-
-# Dry run
-complete -c fabric -l dry-run -d "Show what would be sent to the model without actually sending it"
-
-# Server options
-complete -c fabric -l serve -d "Serve the Fabric Rest API"
-complete -c fabric -l serveOllama -d "Serve the Fabric Rest API with ollama endpoints"
-complete -c fabric -l address -x -d "The address to bind the REST API (default: :8080)"
-complete -c fabric -l api-key -x -d "API key used to secure server routes"
-
-# Config file
-complete -c fabric -l config -r -F -d "Path to YAML config file"
-
-# Version
-complete -c fabric -l version -d "Print current version"
-
-# Extensions
-complete -c fabric -l listextensions -d "List all registered extensions"
-complete -c fabric -l addextension -r -F -d "Register a new extension from config file path"
-complete -c fabric -l rmextension -x -a "(__fabric_extensions)" -d "Remove a registered extension by name"
-
-# Strategy
-complete -c fabric -l strategy -x -a "(__fabric_strategies)" -d "Choose a strategy from the available strategies"
-complete -c fabric -l liststrategies -d "List all strategies"

completions/_fabric

@@ -0,0 +1,111 @@
+#compdef fabric
+
+# Zsh completion for fabric CLI
+# Place this file in a directory in your $fpath (e.g. /usr/local/share/zsh/site-functions)
+
+_fabric_patterns() {
+  local -a patterns
+  patterns=(${(f)"$(fabric --listpatterns --shell-complete-list 2>/dev/null)"})
+  compadd -X "Patterns:" ${patterns}
+}
+
+_fabric_models() {
+  local -a models
+  models=(${(f)"$(fabric --listmodels --shell-complete-list 2>/dev/null)"})
+  compadd -X "Models:" ${models}
+}
+_fabric_contexts() {
+  local -a contexts
+  contexts=(${(f)"$(fabric --listcontexts --shell-complete-list 2>/dev/null)"})
+  compadd -X "Contexts:" ${contexts}
+}
+_fabric_sessions() {
+  local -a sessions
+  sessions=(${(f)"$(fabric --listsessions --shell-complete-list 2>/dev/null)"})
+  compadd -X "Sessions:" ${sessions}
+}
+_fabric_strategies() {
+  local -a strategies
+  strategies=(${(f)"$(fabric --liststrategies --shell-complete-list 2>/dev/null)"})
+  compadd -X "Strategies:" ${strategies}
+}
+
+_fabric_extensions() {
+  local -a extensions
+  extensions=(${(f)"$(fabric --listextensions --shell-complete-list 2>/dev/null)"})
+  compadd -X "Extensions:" ${extensions}
+    '(-L --listmodels)'{-L,--listmodels}'[List all available models]:list models:_fabric_models' \
+    '(-x --listcontexts)'{-x,--listcontexts}'[List all contexts]:list contexts:_fabric_contexts' \
+    '(-X --listsessions)'{-X,--listsessions}'[List all sessions]:list sessions:_fabric_sessions' \
+    '(--listextensions)--listextensions[List all registered extensions]' \
+    '(--liststrategies)--liststrategies[List all strategies]:list strategies:_fabric_strategies' \
+    '(--listvendors)--listvendors[List all vendors]' \
+  vendors=(${(f)"$(fabric --listvendors 2>/dev/null)"})
+  compadd -X "Vendors:" ${vendors}
+}
+
+_fabric() {
+  local curcontext="$curcontext" state line
+  typeset -A opt_args
+
+  _arguments -C \
+    '(-p --pattern)'{-p,--pattern}'[Choose a pattern from the available patterns]:pattern:_fabric_patterns' \
+    '(-v --variable)'{-v,--variable}'[Values for pattern variables, e.g. -v=#role:expert -v=#points:30]:variable:' \
+    '(-C --context)'{-C,--context}'[Choose a context from the available contexts]:context:_fabric_contexts' \
+    '(--session)--session[Choose a session from the available sessions]:session:_fabric_sessions' \
+    '(-a --attachment)'{-a,--attachment}'[Attachment path or URL (e.g. for OpenAI image recognition messages)]:file:_files' \
+    '(-S --setup)'{-S,--setup}'[Run setup for all reconfigurable parts of fabric]' \
+    '(-t --temperature)'{-t,--temperature}'[Set temperature (default: 0.7)]:temperature:' \
+    '(-T --topp)'{-T,--topp}'[Set top P (default: 0.9)]:topp:' \
+    '(-s --stream)'{-s,--stream}'[Stream]' \
+    '(-P --presencepenalty)'{-P,--presencepenalty}'[Set presence penalty (default: 0.0)]:presence penalty:' \
+    '(-r --raw)'{-r,--raw}'[Use the defaults of the model without sending chat options]' \
+    '(-F --frequencypenalty)'{-F,--frequencypenalty}'[Set frequency penalty (default: 0.0)]:frequency penalty:' \
+    '(-l --listpatterns)'{-l,--listpatterns}'[List all patterns]' \
+    '(-L --listmodels)'{-L,--listmodels}'[List all available models]' \
+    '(-x --listcontexts)'{-x,--listcontexts}'[List all contexts]' \
+    '(-X --listsessions)'{-X,--listsessions}'[List all sessions]' \
+    '(-U --updatepatterns)'{-U,--updatepatterns}'[Update patterns]' \
+    '(-c --copy)'{-c,--copy}'[Copy to clipboard]' \
+    '(-m --model)'{-m,--model}'[Choose model]:model:_fabric_models' \
+    '(--modelContextLength)--modelContextLength[Model context length (only affects ollama)]:length:' \
+    '(-o --output)'{-o,--output}'[Output to file]:file:_files' \
+    '(--output-session)--output-session[Output the entire session to the output file]' \
+    '(-n --latest)'{-n,--latest}'[Number of latest patterns to list (default: 0)]:number:' \
+    '(-d --changeDefaultModel)'{-d,--changeDefaultModel}'[Change default model]' \
+    '(-y --youtube)'{-y,--youtube}'[YouTube video or play list URL]:youtube url:' \
+    '(--playlist)--playlist[Prefer playlist over video if both ids are present in the URL]' \
+    '(--transcript)--transcript[Grab transcript from YouTube video and send to chat]' \
+    '(--transcript-with-timestamps)--transcript-with-timestamps[Grab transcript from YouTube video with timestamps]' \
+    '(--comments)--comments[Grab comments from YouTube video and send to chat]' \
+    '(--metadata)--metadata[Output video metadata]' \
+    '(-g --language)'{-g,--language}'[Specify the Language Code for the chat, e.g. -g=en -g=zh]:language:' \
+    '(-u --scrape_url)'{-u,--scrape_url}'[Scrape website URL to markdown using Jina AI]:url:' \
+    '(-q --scrape_question)'{-q,--scrape_question}'[Search question using Jina AI]:question:' \
+    '(-e --seed)'{-e,--seed}'[Seed to be used for LMM generation]:seed:' \
+    '(-w --wipecontext)'{-w,--wipecontext}'[Wipe context]:context:_fabric_contexts' \
+    '(-W --wipesession)'{-W,--wipesession}'[Wipe session]:session:_fabric_sessions' \
+    '(--printcontext)--printcontext[Print context]:context:_fabric_contexts' \
+    '(--printsession)--printsession[Print session]:session:_fabric_sessions' \
+    '(--readability)--readability[Convert HTML input into a clean, readable view]' \
+    '(--input-has-vars)--input-has-vars[Apply variables to user input]' \
+    '(--dry-run)--dry-run[Show what would be sent to the model without actually sending it]' \
+    '(--serve)--serve[Serve the Fabric Rest API]' \
+    '(--serveOllama)--serveOllama[Serve the Fabric Rest API with ollama endpoints]' \
+    '(--address)--address[The address to bind the REST API (default: :8080)]:address:' \
+    '(--api-key)--api-key[API key used to secure server routes]:api-key:' \
+    '(--config)--config[Path to YAML config file]:config file:_files -g "*.yaml *.yml"' \
+    '(--version)--version[Print current version]' \
+    '(--listextensions)--listextensions[List all registered extensions]' \
+    '(--addextension)--addextension[Register a new extension from config file path]:config file:_files -g "*.yaml *.yml"' \
+    '(--rmextension)--rmextension[Remove a registered extension by name]:extension:_fabric_extensions' \
+    '(--strategy)--strategy[Choose a strategy from the available strategies]:strategy:_fabric_strategies' \
+    '(--liststrategies)--liststrategies[List all strategies]' \
+    '(--listvendors)--listvendors[List all vendors]' \
+    '(--shell-complete-list)--shell-complete-list[Output raw list without headers/formatting (for shell completion)]' \
+    '(-h --help)'{-h,--help}'[Show this help message]' \
+    '*:arguments:'
+}
+
+_fabric "$@"
+

completions/fabric.bash

@@ -0,0 +1,90 @@
+# Bash completion for fabric CLI
+#
+# Installation:
+# 1. Place this file in a standard completion directory, e.g.,
+#    - /etc/bash_completion.d/
+#    - /usr/local/etc/bash_completion.d/
+#    - ~/.local/share/bash-completion/completions/
+# 2. Or, source it directly in your ~/.bashrc or ~/.bash_profile:
+#    source /path/to/fabric.bash
+
+_fabric() {
+  local cur prev words cword
+  _get_comp_words_by_ref -n : cur prev words cword
+
+  # Define all possible options/flags
+  local opts="--pattern -p --variable -v --context -C --session --attachment -a --setup -S --temperature -t --topp -T --stream -s --presencepenalty -P --raw -r --frequencypenalty -F --listpatterns -l --listmodels -L --listcontexts -x --listsessions -X --updatepatterns -U --copy -c --model -m --modelContextLength --output -o --output-session --latest -n --changeDefaultModel -d --youtube -y --playlist --transcript --transcript-with-timestamps --comments --metadata --language -g --scrape_url -u --scrape_question -q --seed -e --wipecontext -w --wipesession -W --printcontext --printsession --readability --input-has-vars --dry-run --serve --serveOllama --address --api-key --config --version --listextensions --addextension --rmextension --strategy --liststrategies --listvendors --shell-complete-list --help -h"
+
+  # Helper function for dynamic completions
+  _fabric_get_list() {
+    fabric "$1" --shell-complete-list 2>/dev/null
+  }
+
+  # Handle completions based on the previous word
+  case "${prev}" in
+  -p | --pattern)
+    COMPREPLY=($(compgen -W "$(_fabric_get_list --listpatterns)" -- "${cur}"))
+    return 0
+    ;;
+  -C | --context)
+    COMPREPLY=($(compgen -W "$(_fabric_get_list --listcontexts)" -- "${cur}"))
+    return 0
+    ;;
+  --session)
+    COMPREPLY=($(compgen -W "$(_fabric_get_list --listsessions)" -- "${cur}"))
+    return 0
+    ;;
+  -m | --model)
+    COMPREPLY=($(compgen -W "$(_fabric_get_list --listmodels)" -- "${cur}"))
+    return 0
+    ;;
+  -w | --wipecontext)
+    COMPREPLY=($(compgen -W "$(_fabric_get_list --listcontexts)" -- "${cur}"))
+    return 0
+    ;;
+  -W | --wipesession)
+    COMPREPLY=($(compgen -W "$(_fabric_get_list --listsessions)" -- "${cur}"))
+    return 0
+    ;;
+  --printcontext)
+    COMPREPLY=($(compgen -W "$(_fabric_get_list --listcontexts)" -- "${cur}"))
+    return 0
+    ;;
+  --printsession)
+    COMPREPLY=($(compgen -W "$(_fabric_get_list --listsessions)" -- "${cur}"))
+    return 0
+    ;;
+  --rmextension)
+    COMPREPLY=($(compgen -W "$(_fabric_get_list --listextensions)" -- "${cur}"))
+    return 0
+    ;;
+  --strategy)
+    COMPREPLY=($(compgen -W "$(_fabric_get_list --liststrategies)" -- "${cur}"))
+    return 0
+    ;;
+  # Options requiring file/directory paths
+  -a | --attachment | -o | --output | --config | --addextension)
+    _filedir
+    return 0
+    ;;
+  # Options requiring simple arguments (no specific completion logic here)
+  -v | --variable | -t | --temperature | -T | --topp | -P | --presencepenalty | -F | --frequencypenalty | --modelContextLength | -n | --latest | -y | --youtube | -g | --language | -u | --scrape_url | -q | --scrape_question | -e | --seed | --address | --api-key)
+    # No specific completion suggestions, user types the value
+    return 0
+    ;;
+  esac
+
+  # If the current word starts with '-', suggest options
+  if [[ "${cur}" == -* ]]; then
+    COMPREPLY=($(compgen -W "${opts}" -- "${cur}"))
+    return 0
+  fi
+
+  # Default: complete files/directories if no other rule matches
+  # _filedir
+  # Or provide no completions if it's not an option or argument following a known flag
+  COMPREPLY=()
+
+}
+
+complete -F _fabric fabric

completions/fabric.fish

@@ -0,0 +1,94 @@
+# Fish shell completion for fabric CLI
+#
+# Installation:
+# Copy this file to ~/.config/fish/completions/fabric.fish
+# or run:
+# mkdir -p ~/.config/fish/completions
+# cp completions/fabric.fish ~/.config/fish/completions/
+
+# Helper functions for dynamic completions
+function __fabric_get_patterns
+	fabric --listpatterns --shell-complete-list 2>/dev/null
+end
+
+function __fabric_get_models
+	fabric --listmodels --shell-complete-list 2>/dev/null
+end
+
+function __fabric_get_contexts
+	fabric --listcontexts --shell-complete-list 2>/dev/null
+end
+
+function __fabric_get_sessions
+	fabric --listsessions --shell-complete-list 2>/dev/null
+end
+
+function __fabric_get_strategies
+	fabric --liststrategies --shell-complete-list 2>/dev/null
+end
+
+function __fabric_get_extensions
+	fabric --listextensions --shell-complete-list 2>/dev/null
+end
+
+# Main completion function
+complete -c fabric -f
+
+# Flag completions with arguments
+complete -c fabric -s p -l pattern -d "Choose a pattern from the available patterns" -a "(__fabric_get_patterns)"
+complete -c fabric -s v -l variable -d "Values for pattern variables, e.g. -v=#role:expert -v=#points:30"
+complete -c fabric -s C -l context -d "Choose a context from the available contexts" -a "(__fabric_get_contexts)"
+complete -c fabric -l session -d "Choose a session from the available sessions" -a "(__fabric_get_sessions)"
+complete -c fabric -s a -l attachment -d "Attachment path or URL (e.g. for OpenAI image recognition messages)" -r
+complete -c fabric -s t -l temperature -d "Set temperature (default: 0.7)"
+complete -c fabric -s T -l topp -d "Set top P (default: 0.9)"
+complete -c fabric -s P -l presencepenalty -d "Set presence penalty (default: 0.0)"
+complete -c fabric -s F -l frequencypenalty -d "Set frequency penalty (default: 0.0)"
+complete -c fabric -s m -l model -d "Choose model" -a "(__fabric_get_models)"
+complete -c fabric -l modelContextLength -d "Model context length (only affects ollama)"
+complete -c fabric -s o -l output -d "Output to file" -r
+complete -c fabric -s n -l latest -d "Number of latest patterns to list (default: 0)"
+complete -c fabric -s y -l youtube -d "YouTube video or play list URL to grab transcript, comments from it"
+complete -c fabric -s g -l language -d "Specify the Language Code for the chat, e.g. -g=en -g=zh"
+complete -c fabric -s u -l scrape_url -d "Scrape website URL to markdown using Jina AI"
+complete -c fabric -s q -l scrape_question -d "Search question using Jina AI"
+complete -c fabric -s e -l seed -d "Seed to be used for LMM generation"
+complete -c fabric -s w -l wipecontext -d "Wipe context" -a "(__fabric_get_contexts)"
+complete -c fabric -s W -l wipesession -d "Wipe session" -a "(__fabric_get_sessions)"
+complete -c fabric -l printcontext -d "Print context" -a "(__fabric_get_contexts)"
+complete -c fabric -l printsession -d "Print session" -a "(__fabric_get_sessions)"
+complete -c fabric -l address -d "The address to bind the REST API (default: :8080)"
+complete -c fabric -l api-key -d "API key used to secure server routes"
+complete -c fabric -l config -d "Path to YAML config file" -r -a "*.yaml *.yml"
+complete -c fabric -l addextension -d "Register a new extension from config file path" -r -a "*.yaml *.yml"
+complete -c fabric -l rmextension -d "Remove a registered extension by name" -a "(__fabric_get_extensions)"
+complete -c fabric -l strategy -d "Choose a strategy from the available strategies" -a "(__fabric_get_strategies)"
+
+# Boolean flags (no arguments)
+complete -c fabric -s S -l setup -d "Run setup for all reconfigurable parts of fabric"
+complete -c fabric -s s -l stream -d "Stream"
+complete -c fabric -s r -l raw -d "Use the defaults of the model without sending chat options"
+complete -c fabric -s l -l listpatterns -d "List all patterns"
+complete -c fabric -s L -l listmodels -d "List all available models"
+complete -c fabric -s x -l listcontexts -d "List all contexts"
+complete -c fabric -s X -l listsessions -d "List all sessions"
+complete -c fabric -s U -l updatepatterns -d "Update patterns"
+complete -c fabric -s c -l copy -d "Copy to clipboard"
+complete -c fabric -l output-session -d "Output the entire session to the output file"
+complete -c fabric -s d -l changeDefaultModel -d "Change default model"
+complete -c fabric -l playlist -d "Prefer playlist over video if both ids are present in the URL"
+complete -c fabric -l transcript -d "Grab transcript from YouTube video and send to chat"
+complete -c fabric -l transcript-with-timestamps -d "Grab transcript from YouTube video with timestamps"
+complete -c fabric -l comments -d "Grab comments from YouTube video and send to chat"
+complete -c fabric -l metadata -d "Output video metadata"
+complete -c fabric -l readability -d "Convert HTML input into a clean, readable view"
+complete -c fabric -l input-has-vars -d "Apply variables to user input"
+complete -c fabric -l dry-run -d "Show what would be sent to the model without actually sending it"
+complete -c fabric -l serve -d "Serve the Fabric Rest API"
+complete -c fabric -l serveOllama -d "Serve the Fabric Rest API with ollama endpoints"
+complete -c fabric -l version -d "Print current version"
+complete -c fabric -l listextensions -d "List all registered extensions"
+complete -c fabric -l liststrategies -d "List all strategies"
+complete -c fabric -l listvendors -d "List all vendors"
+complete -c fabric -l shell-complete-list -d "Output raw list without headers/formatting (for shell completion)"
+complete -c fabric -s h -l help -d "Show this help message"

core/chatter.go

@@ -7,7 +7,7 @@ import (
 	"os"
 	"strings"
 
-	goopenai "github.com/sashabaranov/go-openai"
+	"github.com/danielmiessler/fabric/chat"
 
 	"github.com/danielmiessler/fabric/common"
 	"github.com/danielmiessler/fabric/plugins/ai"
@@ -30,8 +30,15 @@ type Chatter struct {
 	strategy           string
 }
 
-// Send processes a chat request and applies any file changes if using the create_coding_feature pattern
+// Send processes a chat request and applies file changes for create_coding_feature pattern
 func (o *Chatter) Send(request *common.ChatRequest, opts *common.ChatOptions) (session *fsdb.Session, err error) {
+	modelToUse := opts.Model
+	if modelToUse == "" {
+		modelToUse = o.model
+	}
+	if o.vendor.NeedsRawMode(modelToUse) {
+		opts.Raw = true
+	}
 	if session, err = o.BuildSession(request, opts.Raw); err != nil {
 		return
 	}
@@ -82,18 +89,15 @@ func (o *Chatter) Send(request *common.ChatRequest, opts *common.ChatOptions) (s
 		return
 	}
 
-	// Process file changes if using the create_coding_feature pattern
+	// Process file changes for create_coding_feature pattern
 	if request.PatternName == "create_coding_feature" {
-		// Look for file changes in the response
 		summary, fileChanges, parseErr := common.ParseFileChanges(message)
 		if parseErr != nil {
 			fmt.Printf("Warning: Failed to parse file changes: %v\n", parseErr)
 		} else if len(fileChanges) > 0 {
-			// Get the project root - use the current directory
 			projectRoot, err := os.Getwd()
 			if err != nil {
 				fmt.Printf("Warning: Failed to get current directory: %v\n", err)
-				// Continue without applying changes
 			} else {
 				if applyErr := common.ApplyFileChanges(projectRoot, fileChanges); applyErr != nil {
 					fmt.Printf("Warning: Failed to apply file changes: %v\n", applyErr)
@@ -106,7 +110,7 @@ func (o *Chatter) Send(request *common.ChatRequest, opts *common.ChatOptions) (s
 		message = summary
 	}
 
-	session.Append(&goopenai.ChatCompletionMessage{Role: goopenai.ChatMessageRoleAssistant, Content: message})
+	session.Append(&chat.ChatCompletionMessage{Role: chat.ChatMessageRoleAssistant, Content: message})
 
 	if session.Name != "" {
 		err = o.db.Sessions.SaveSession(session)
@@ -115,7 +119,6 @@ func (o *Chatter) Send(request *common.ChatRequest, opts *common.ChatOptions) (s
 }
 
 func (o *Chatter) BuildSession(request *common.ChatRequest, raw bool) (session *fsdb.Session, err error) {
-	// If a session name is provided, retrieve it from the database
 	if request.SessionName != "" {
 		var sess *fsdb.Session
 		if sess, err = o.db.Sessions.Get(request.SessionName); err != nil {
@@ -128,7 +131,7 @@ func (o *Chatter) BuildSession(request *common.ChatRequest, raw bool) (session *
 	}
 
 	if request.Meta != "" {
-		session.Append(&goopenai.ChatCompletionMessage{Role: common.ChatMessageRoleMeta, Content: request.Meta})
+		session.Append(&chat.ChatCompletionMessage{Role: common.ChatMessageRoleMeta, Content: request.Meta})
 	}
 
 	// if a context name is provided, retrieve it from the database
@@ -142,12 +145,12 @@ func (o *Chatter) BuildSession(request *common.ChatRequest, raw bool) (session *
 		contextContent = ctx.Content
 	}
 
-	// Process any template variables in the message content (user input)
+	// Process template variables in message content
 	// Double curly braces {{variable}} indicate template substitution
-	// Ensure we have a message before processing, other wise we'll get an error when we pass to pattern.go
+	// Ensure we have a message before processing
 	if request.Message == nil {
-		request.Message = &goopenai.ChatCompletionMessage{
-			Role:    goopenai.ChatMessageRoleUser,
+		request.Message = &chat.ChatCompletionMessage{
+			Role:    chat.ChatMessageRoleUser,
 			Content: " ",
 		}
 	}
@@ -161,19 +164,19 @@ func (o *Chatter) BuildSession(request *common.ChatRequest, raw bool) (session *
 	}
 
 	var patternContent string
+	inputUsed := false
 	if request.PatternName != "" {
 		pattern, err := o.db.Patterns.GetApplyVariables(request.PatternName, request.PatternVariables, request.Message.Content)
-		// pattern will now contain user input, and all variables will be resolved, or errored
 
 		if err != nil {
 			return nil, fmt.Errorf("could not get pattern %s: %v", request.PatternName, err)
 		}
 		patternContent = pattern.Pattern
+		inputUsed = true
 	}
 
 	systemMessage := strings.TrimSpace(contextContent) + strings.TrimSpace(patternContent)
 
-	// Apply strategy if specified
 	if request.StrategyName != "" {
 		strategy, err := strategy.LoadStrategy(request.StrategyName)
 		if err != nil {
@@ -192,26 +195,53 @@ func (o *Chatter) BuildSession(request *common.ChatRequest, raw bool) (session *
 	}
 
 	if raw {
-		// In raw mode, combine system message (potentially with strategy) and user message into a single user message
+		var finalContent string
 		if systemMessage != "" {
-			if request.Message != nil {
-				// Prepend system message to user content, ensuring user input is preserved
-				request.Message.Content = fmt.Sprintf("%s\n\n%s", systemMessage, request.Message.Content)
-				request.Message.Role = goopenai.ChatMessageRoleUser // Ensure role is User in raw mode
+			if request.PatternName != "" {
+				finalContent = systemMessage
 			} else {
-				// If no user message, create one with the system content, marked as User role
-				request.Message = &goopenai.ChatCompletionMessage{Role: goopenai.ChatMessageRoleUser, Content: systemMessage}
+				finalContent = fmt.Sprintf("%s\n\n%s", systemMessage, request.Message.Content)
 			}
-		} // else: no system message, user message (if any) remains unchanged
-	} else {
-		// Not raw mode, append system message separately if it exists
-		if systemMessage != "" {
-			session.Append(&goopenai.ChatCompletionMessage{Role: goopenai.ChatMessageRoleSystem, Content: systemMessage})
-		}
-	}
 
-	if request.Message != nil {
-		session.Append(request.Message)
+			// Handle MultiContent properly in raw mode
+			if len(request.Message.MultiContent) > 0 {
+				// When we have attachments, add the text as a text part in MultiContent
+				newMultiContent := []chat.ChatMessagePart{
+					{
+						Type: chat.ChatMessagePartTypeText,
+						Text: finalContent,
+					},
+				}
+				// Add existing non-text parts (like images)
+				for _, part := range request.Message.MultiContent {
+					if part.Type != chat.ChatMessagePartTypeText {
+						newMultiContent = append(newMultiContent, part)
+					}
+				}
+				request.Message = &chat.ChatCompletionMessage{
+					Role:         chat.ChatMessageRoleUser,
+					MultiContent: newMultiContent,
+				}
+			} else {
+				// No attachments, use regular Content field
+				request.Message = &chat.ChatCompletionMessage{
+					Role:    chat.ChatMessageRoleUser,
+					Content: finalContent,
+				}
+			}
+		}
+		if request.Message != nil {
+			session.Append(request.Message)
+		}
+	} else {
+		if systemMessage != "" {
+			session.Append(&chat.ChatCompletionMessage{Role: chat.ChatMessageRoleSystem, Content: systemMessage})
+		}
+		// If multi-part content, it is in the user message, and should be added.
+		// Otherwise, we should only add it if we have not already used it in the systemMessage.
+		if len(request.Message.MultiContent) > 0 || (request.Message != nil && !inputUsed) {
+			session.Append(request.Message)
+		}
 	}
 
 	if session.IsEmpty() {

core/plugin_registry.go

@@ -10,7 +10,9 @@ import (
 	"strconv"
 	"strings"
 
+	"github.com/danielmiessler/fabric/plugins/ai/bedrock"
 	"github.com/danielmiessler/fabric/plugins/ai/exolab"
+	"github.com/danielmiessler/fabric/plugins/ai/perplexity" // Added Perplexity plugin
 	"github.com/danielmiessler/fabric/plugins/strategy"
 
 	"github.com/samber/lo"
@@ -34,6 +36,33 @@ import (
 	"github.com/danielmiessler/fabric/plugins/tools/youtube"
 )
 
+// hasAWSCredentials checks if any AWS credentials are present either in the
+// environment variables or in the default/shared credentials file. It doesn't
+// attempt to verify the validity of the credentials, but simply ensures that a
+// potential authentication source exists so we can safely initialize the
+// Bedrock client without causing the AWS SDK to search for credentials.
+func hasAWSCredentials() bool {
+	if os.Getenv("AWS_PROFILE") != "" ||
+		os.Getenv("AWS_ROLE_SESSION_NAME") != "" ||
+		(os.Getenv("AWS_ACCESS_KEY_ID") != "" && os.Getenv("AWS_SECRET_ACCESS_KEY") != "") {
+
+		return true
+	}
+
+	credFile := os.Getenv("AWS_SHARED_CREDENTIALS_FILE")
+	if credFile == "" {
+		if home, err := os.UserHomeDir(); err == nil {
+			credFile = filepath.Join(home, ".aws", "credentials")
+		}
+	}
+	if credFile != "" {
+		if _, err := os.Stat(credFile); err == nil {
+			return true
+		}
+	}
+	return false
+}
+
 func NewPluginRegistry(db *fsdb.Db) (ret *PluginRegistry, err error) {
 	ret = &PluginRegistry{
 		Db:             db,
@@ -66,8 +95,13 @@ func NewPluginRegistry(db *fsdb.Db) (ret *PluginRegistry, err error) {
 		anthropic.NewClient(),
 		lmstudio.NewClient(),
 		exolab.NewClient(),
+		perplexity.NewClient(), // Added Perplexity client
 	)
 
+	if hasAWSCredentials() {
+		vendors = append(vendors, bedrock.NewClient())
+	}
+
 	// Add all OpenAI-compatible providers
 	for providerName := range openai_compatible.ProviderMap {
 		provider, _ := openai_compatible.GetProviderByName(providerName)
@@ -152,7 +186,7 @@ func (o *PluginRegistry) Setup() (err error) {
 	groupsPlugins.AddGroupItems("Tools", o.Defaults, o.Jina, o.Language, o.PatternsLoader, o.Strategies, o.YouTube)
 
 	for {
-		groupsPlugins.Print()
+		groupsPlugins.Print(false)
 
 		if answerErr := setupQuestion.Ask("Plugin Number"); answerErr != nil {
 			break

go.mod

@@ -5,41 +5,57 @@ go 1.24.0
 toolchain go1.24.2
 
 require (
-	github.com/anaskhan96/soup v1.2.5
-	github.com/anthropics/anthropic-sdk-go v0.2.0-beta.3
+	github.com/anthropics/anthropic-sdk-go v1.4.0
 	github.com/atotto/clipboard v0.1.4
+	github.com/aws/aws-sdk-go-v2 v1.36.4
+	github.com/aws/aws-sdk-go-v2/config v1.27.27
+	github.com/aws/aws-sdk-go-v2/service/bedrock v1.34.1
+	github.com/aws/aws-sdk-go-v2/service/bedrockruntime v1.30.0
 	github.com/gabriel-vasile/mimetype v1.4.9
-	github.com/gin-gonic/gin v1.10.0
-	github.com/go-git/go-git/v5 v5.16.0
+	github.com/gin-gonic/gin v1.10.1
+	github.com/go-git/go-git/v5 v5.16.2
 	github.com/go-shiori/go-readability v0.0.0-20250217085726-9f5bf5ca7612
-	github.com/google/generative-ai-go v0.19.0
+	github.com/google/generative-ai-go v0.20.1
 	github.com/jessevdk/go-flags v1.6.1
 	github.com/joho/godotenv v1.5.1
-	github.com/ollama/ollama v0.6.6
+	github.com/ollama/ollama v0.9.0
+	github.com/openai/openai-go v1.8.2
 	github.com/otiai10/copy v1.14.1
 	github.com/pkg/errors v0.9.1
-	github.com/samber/lo v1.49.1
-	github.com/sashabaranov/go-openai v1.38.2
+	github.com/samber/lo v1.50.0
+	github.com/sgaunet/perplexity-go/v2 v2.8.0
 	github.com/stretchr/testify v1.10.0
-	golang.org/x/text v0.24.0
-	google.golang.org/api v0.230.0
+	golang.org/x/text v0.26.0
+	google.golang.org/api v0.236.0
 	gopkg.in/yaml.v2 v2.4.0
 	gopkg.in/yaml.v3 v3.0.1
 )
 
 require (
-	cloud.google.com/go v0.120.1 // indirect
-	cloud.google.com/go/ai v0.10.2 // indirect
-	cloud.google.com/go/auth v0.16.1 // indirect
+	cloud.google.com/go v0.121.2 // indirect
+	cloud.google.com/go/ai v0.12.1 // indirect
+	cloud.google.com/go/auth v0.16.2 // indirect
 	cloud.google.com/go/auth/oauth2adapt v0.2.8 // indirect
-	cloud.google.com/go/compute/metadata v0.6.0 // indirect
+	cloud.google.com/go/compute/metadata v0.7.0 // indirect
 	cloud.google.com/go/longrunning v0.6.7 // indirect
-	dario.cat/mergo v1.0.1 // indirect
+	dario.cat/mergo v1.0.2 // indirect
 	github.com/Microsoft/go-winio v0.6.2 // indirect
-	github.com/ProtonMail/go-crypto v1.2.0 // indirect
+	github.com/ProtonMail/go-crypto v1.3.0 // indirect
 	github.com/andybalholm/cascadia v1.3.3 // indirect
 	github.com/araddon/dateparse v0.0.0-20210429162001-6b43995a97de // indirect
-	github.com/bytedance/sonic v1.13.2 // indirect
+	github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.6.10 // indirect
+	github.com/aws/aws-sdk-go-v2/credentials v1.17.27 // indirect
+	github.com/aws/aws-sdk-go-v2/feature/ec2/imds v1.16.11 // indirect
+	github.com/aws/aws-sdk-go-v2/internal/configsources v1.3.35 // indirect
+	github.com/aws/aws-sdk-go-v2/internal/endpoints/v2 v2.6.35 // indirect
+	github.com/aws/aws-sdk-go-v2/internal/ini v1.8.0 // indirect
+	github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding v1.11.3 // indirect
+	github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.11.17 // indirect
+	github.com/aws/aws-sdk-go-v2/service/sso v1.22.4 // indirect
+	github.com/aws/aws-sdk-go-v2/service/ssooidc v1.26.4 // indirect
+	github.com/aws/aws-sdk-go-v2/service/sts v1.30.3 // indirect
+	github.com/aws/smithy-go v1.22.2 // indirect
+	github.com/bytedance/sonic v1.13.3 // indirect
 	github.com/bytedance/sonic/loader v0.2.4 // indirect
 	github.com/cloudflare/circl v1.6.1 // indirect
 	github.com/cloudwego/base64x v0.1.5 // indirect
@@ -50,7 +66,7 @@ require (
 	github.com/gin-contrib/sse v1.1.0 // indirect
 	github.com/go-git/gcfg v1.5.1-0.20230307220236-3a3c6141e376 // indirect
 	github.com/go-git/go-billy/v5 v5.6.2 // indirect
-	github.com/go-logr/logr v1.4.2 // indirect
+	github.com/go-logr/logr v1.4.3 // indirect
 	github.com/go-logr/stdr v1.2.2 // indirect
 	github.com/go-playground/locales v0.14.1 // indirect
 	github.com/go-playground/universal-translator v0.18.1 // indirect
@@ -62,7 +78,7 @@ require (
 	github.com/google/s2a-go v0.1.9 // indirect
 	github.com/google/uuid v1.6.0 // indirect
 	github.com/googleapis/enterprise-certificate-proxy v0.3.6 // indirect
-	github.com/googleapis/gax-go/v2 v2.14.1 // indirect
+	github.com/googleapis/gax-go/v2 v2.14.2 // indirect
 	github.com/jbenet/go-context v0.0.0-20150711004518-d14ea06fba99 // indirect
 	github.com/json-iterator/go v1.1.12 // indirect
 	github.com/kevinburke/ssh_config v1.2.0 // indirect
@@ -75,31 +91,31 @@ require (
 	github.com/pelletier/go-toml/v2 v2.2.4 // indirect
 	github.com/pjbgf/sha1cd v0.3.2 // indirect
 	github.com/pmezard/go-difflib v1.0.0 // indirect
-	github.com/sergi/go-diff v1.3.2-0.20230802210424-5b0b94c5c0d3 // indirect
+	github.com/sergi/go-diff v1.4.0 // indirect
 	github.com/skeema/knownhosts v1.3.1 // indirect
 	github.com/tidwall/gjson v1.18.0 // indirect
 	github.com/tidwall/match v1.1.1 // indirect
 	github.com/tidwall/pretty v1.2.1 // indirect
 	github.com/tidwall/sjson v1.2.5 // indirect
 	github.com/twitchyliquid64/golang-asm v0.15.1 // indirect
-	github.com/ugorji/go/codec v1.2.12 // indirect
+	github.com/ugorji/go/codec v1.2.14 // indirect
 	github.com/xanzy/ssh-agent v0.3.3 // indirect
 	go.opentelemetry.io/auto/sdk v1.1.0 // indirect
-	go.opentelemetry.io/contrib/instrumentation/google.golang.org/grpc/otelgrpc v0.60.0 // indirect
-	go.opentelemetry.io/contrib/instrumentation/net/http/otelhttp v0.60.0 // indirect
-	go.opentelemetry.io/otel v1.35.0 // indirect
-	go.opentelemetry.io/otel/metric v1.35.0 // indirect
-	go.opentelemetry.io/otel/trace v1.35.0 // indirect
-	golang.org/x/arch v0.16.0 // indirect
-	golang.org/x/crypto v0.37.0 // indirect
-	golang.org/x/net v0.39.0 // indirect
-	golang.org/x/oauth2 v0.29.0 // indirect
-	golang.org/x/sync v0.13.0 // indirect
-	golang.org/x/sys v0.32.0 // indirect
-	golang.org/x/time v0.11.0 // indirect
-	google.golang.org/genproto/googleapis/api v0.0.0-20250422160041-2d3770c4ea7f // indirect
-	google.golang.org/genproto/googleapis/rpc v0.0.0-20250422160041-2d3770c4ea7f // indirect
-	google.golang.org/grpc v1.72.0 // indirect
+	go.opentelemetry.io/contrib/instrumentation/google.golang.org/grpc/otelgrpc v0.61.0 // indirect
+	go.opentelemetry.io/contrib/instrumentation/net/http/otelhttp v0.61.0 // indirect
+	go.opentelemetry.io/otel v1.36.0 // indirect
+	go.opentelemetry.io/otel/metric v1.36.0 // indirect
+	go.opentelemetry.io/otel/trace v1.36.0 // indirect
+	golang.org/x/arch v0.18.0 // indirect
+	golang.org/x/crypto v0.39.0 // indirect
+	golang.org/x/net v0.41.0 // indirect
+	golang.org/x/oauth2 v0.30.0 // indirect
+	golang.org/x/sync v0.15.0 // indirect
+	golang.org/x/sys v0.33.0 // indirect
+	golang.org/x/time v0.12.0 // indirect
+	google.golang.org/genproto/googleapis/api v0.0.0-20250603155806-513f23925822 // indirect
+	google.golang.org/genproto/googleapis/rpc v0.0.0-20250603155806-513f23925822 // indirect
+	google.golang.org/grpc v1.73.0 // indirect
 	google.golang.org/protobuf v1.36.6 // indirect
 	gopkg.in/warnings.v0 v0.1.2 // indirect
 )

go.sum

@@ -1,38 +1,68 @@
-cloud.google.com/go v0.120.1 h1:Z+5V7yd383+9617XDCyszmK5E4wJRJL+tquMfDj9hLM=
-cloud.google.com/go v0.120.1/go.mod h1:56Vs7sf/i2jYM6ZL9NYlC82r04PThNcPS5YgFmb0rp8=
-cloud.google.com/go/ai v0.10.2 h1:5NHzmZlRs+3kvlsVdjT0cTnLrjQdROJ/8VOljVfs+8o=
-cloud.google.com/go/ai v0.10.2/go.mod h1:xZuZuE9d3RgsR132meCnPadiU9XV0qXjpLr+P4J46eE=
-cloud.google.com/go/auth v0.16.1 h1:XrXauHMd30LhQYVRHLGvJiYeczweKQXZxsTbV9TiguU=
-cloud.google.com/go/auth v0.16.1/go.mod h1:1howDHJ5IETh/LwYs3ZxvlkXF48aSqqJUM+5o02dNOI=
+cloud.google.com/go v0.121.2 h1:v2qQpN6Dx9x2NmwrqlesOt3Ys4ol5/lFZ6Mg1B7OJCg=
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+cloud.google.com/go/ai v0.12.1 h1:m1n/VjUuHS+pEO/2R4/VbuuEIkgk0w67fDQvFaMngM0=
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+cloud.google.com/go/auth v0.16.2 h1:QvBAGFPLrDeoiNjyfVunhQ10HKNYuOwZ5noee0M5df4=
+cloud.google.com/go/auth v0.16.2/go.mod h1:sRBas2Y1fB1vZTdurouM0AzuYQBMZinrUYL8EufhtEA=
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-cloud.google.com/go/compute/metadata v0.6.0 h1:A6hENjEsCDtC1k8byVsgwvVcioamEHvZ4j01OwKxG9I=
-cloud.google.com/go/compute/metadata v0.6.0/go.mod h1:FjyFAW1MW0C203CEOMDTu3Dk1FlqW3Rga40jzHL4hfg=
+cloud.google.com/go/compute/metadata v0.7.0 h1:PBWF+iiAerVNe8UCHxdOt6eHLVc3ydFeOCw78U8ytSU=
+cloud.google.com/go/compute/metadata v0.7.0/go.mod h1:j5MvL9PprKL39t166CoB1uVHfQMs4tFQZZcKwksXUjo=
 cloud.google.com/go/longrunning v0.6.7 h1:IGtfDWHhQCgCjwQjV9iiLnUta9LBCo8R9QmAFsS/PrE=
 cloud.google.com/go/longrunning v0.6.7/go.mod h1:EAFV3IZAKmM56TyiE6VAP3VoTzhZzySwI/YI1s/nRsY=
-dario.cat/mergo v1.0.1 h1:Ra4+bf83h2ztPIQYNP99R6m+Y7KfnARDfID+a+vLl4s=
-dario.cat/mergo v1.0.1/go.mod h1:uNxQE+84aUszobStD9th8a29P2fMDhsBdgRYvZOxGmk=
+dario.cat/mergo v1.0.2 h1:85+piFYR1tMbRrLcDwR18y4UKJ3aH1Tbzi24VRW1TK8=
+dario.cat/mergo v1.0.2/go.mod h1:E/hbnu0NxMFBjpMIE34DRGLWqDy0g5FuKDhCb31ngxA=
 github.com/Microsoft/go-winio v0.5.2/go.mod h1:WpS1mjBmmwHBEWmogvA2mj8546UReBk4v8QkMxJ6pZY=
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 github.com/Microsoft/go-winio v0.6.2/go.mod h1:yd8OoFMLzJbo9gZq8j5qaps8bJ9aShtEA8Ipt1oGCvU=
-github.com/ProtonMail/go-crypto v1.2.0 h1:+PhXXn4SPGd+qk76TlEePBfOfivE0zkWFenhGhFLzWs=
-github.com/ProtonMail/go-crypto v1.2.0/go.mod h1:9whxjD8Rbs29b4XWbB8irEcE8KHMqaR2e7GWU1R+/PE=
-github.com/anaskhan96/soup v1.2.5 h1:V/FHiusdTrPrdF4iA1YkVxsOpdNcgvqT1hG+YtcZ5hM=
-github.com/anaskhan96/soup v1.2.5/go.mod h1:6YnEp9A2yywlYdM4EgDz9NEHclocMepEtku7wg6Cq3s=
+github.com/ProtonMail/go-crypto v1.3.0 h1:ILq8+Sf5If5DCpHQp4PbZdS1J7HDFRXz/+xKBiRGFrw=
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 github.com/andybalholm/cascadia v1.3.3/go.mod h1:xNd9bqTn98Ln4DwST8/nG+H0yuB8Hmgu1YHNnWw0GeA=
 github.com/anmitsu/go-shlex v0.0.0-20200514113438-38f4b401e2be h1:9AeTilPcZAjCFIImctFaOjnTIavg87rW78vTPkQqLI8=
 github.com/anmitsu/go-shlex v0.0.0-20200514113438-38f4b401e2be/go.mod h1:ySMOLuWl6zY27l47sB3qLNK6tF2fkHG55UZxx8oIVo4=
-github.com/anthropics/anthropic-sdk-go v0.2.0-beta.3 h1:b5t1ZJMvV/l99y4jbz7kRFdUp3BSDkI8EhSlHczivtw=
-github.com/anthropics/anthropic-sdk-go v0.2.0-beta.3/go.mod h1:AapDW22irxK2PSumZiQXYUFvsdQgkwIWlpESweWZI/c=
+github.com/anthropics/anthropic-sdk-go v1.4.0 h1:fU1jKxYbQdQDiEXCxeW5XZRIOwKevn/PMg8Ay1nnUx0=
+github.com/anthropics/anthropic-sdk-go v1.4.0/go.mod h1:AapDW22irxK2PSumZiQXYUFvsdQgkwIWlpESweWZI/c=
 github.com/araddon/dateparse v0.0.0-20210429162001-6b43995a97de h1:FxWPpzIjnTlhPwqqXc4/vE0f7GvRjuAsbW+HOIe8KnA=
 github.com/araddon/dateparse v0.0.0-20210429162001-6b43995a97de/go.mod h1:DCaWoUhZrYW9p1lxo/cm8EmUOOzAPSEZNGF2DK1dJgw=
 github.com/armon/go-socks5 v0.0.0-20160902184237-e75332964ef5 h1:0CwZNZbxp69SHPdPJAN/hZIm0C4OItdklCFmMRWYpio=
 github.com/armon/go-socks5 v0.0.0-20160902184237-e75332964ef5/go.mod h1:wHh0iHkYZB8zMSxRWpUBQtwG5a7fFgvEO+odwuTv2gs=
 github.com/atotto/clipboard v0.1.4 h1:EH0zSVneZPSuFR11BlR9YppQTVDbh5+16AmcJi4g1z4=
 github.com/atotto/clipboard v0.1.4/go.mod h1:ZY9tmq7sm5xIbd9bOK4onWV4S6X0u6GY7Vn0Yu86PYI=
-github.com/bytedance/sonic v1.13.2 h1:8/H1FempDZqC4VqjptGo14QQlJx8VdZJegxs6wwfqpQ=
-github.com/bytedance/sonic v1.13.2/go.mod h1:o68xyaF9u2gvVBuGHPlUVCy+ZfmNNO5ETf1+KgkJhz4=
+github.com/aws/aws-sdk-go-v2 v1.36.4 h1:GySzjhVvx0ERP6eyfAbAuAXLtAda5TEy19E5q5W8I9E=
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+github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream v1.6.10 h1:zAybnyUQXIZ5mok5Jqwlf58/TFE7uvd3IAsa1aF9cXs=
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+github.com/aws/aws-sdk-go-v2/config v1.27.27 h1:HdqgGt1OAP0HkEDDShEl0oSYa9ZZBSOmKpdpsDMdO90=
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+github.com/aws/aws-sdk-go-v2/credentials v1.17.27 h1:2raNba6gr2IfA0eqqiP2XiQ0UVOpGPgDSi0I9iAP+UI=
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+github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.11.17 h1:HGErhhrxZlQ044RiM+WdoZxp0p+EGM62y3L6pwA4olE=
+github.com/aws/aws-sdk-go-v2/service/internal/presigned-url v1.11.17/go.mod h1:RkZEx4l0EHYDJpWppMJ3nD9wZJAa8/0lq9aVC+r2UII=
+github.com/aws/aws-sdk-go-v2/service/sso v1.22.4 h1:BXx0ZIxvrJdSgSvKTZ+yRBeSqqgPM89VPlulEcl37tM=
+github.com/aws/aws-sdk-go-v2/service/sso v1.22.4/go.mod h1:ooyCOXjvJEsUw7x+ZDHeISPMhtwI3ZCB7ggFMcFfWLU=
+github.com/aws/aws-sdk-go-v2/service/ssooidc v1.26.4 h1:yiwVzJW2ZxZTurVbYWA7QOrAaCYQR72t0wrSBfoesUE=
+github.com/aws/aws-sdk-go-v2/service/ssooidc v1.26.4/go.mod h1:0oxfLkpz3rQ/CHlx5hB7H69YUpFiI1tql6Q6Ne+1bCw=
+github.com/aws/aws-sdk-go-v2/service/sts v1.30.3 h1:ZsDKRLXGWHk8WdtyYMoGNO7bTudrvuKpDKgMVRlepGE=
+github.com/aws/aws-sdk-go-v2/service/sts v1.30.3/go.mod h1:zwySh8fpFyXp9yOr/KVzxOl8SRqgf/IDw5aUt9UKFcQ=
+github.com/aws/smithy-go v1.22.2 h1:6D9hW43xKFrRx/tXXfAlIZc4JI+yQe6snnWcQyxSyLQ=
+github.com/aws/smithy-go v1.22.2/go.mod h1:irrKGvNn1InZwb2d7fkIRNucdfwR8R+Ts3wxYa/cJHg=
+github.com/bytedance/sonic v1.13.3 h1:MS8gmaH16Gtirygw7jV91pDCN33NyMrPbN7qiYhEsF0=
+github.com/bytedance/sonic v1.13.3/go.mod h1:o68xyaF9u2gvVBuGHPlUVCy+ZfmNNO5ETf1+KgkJhz4=
 github.com/bytedance/sonic/loader v0.1.1/go.mod h1:ncP89zfokxS5LZrJxl5z0UJcsk4M4yY2JpfqGeCtNLU=
 github.com/bytedance/sonic/loader v0.2.4 h1:ZWCw4stuXUsn1/+zQDqeE7JKP+QO47tz7QCNan80NzY=
 github.com/bytedance/sonic/loader v0.2.4/go.mod h1:N8A3vUdtUebEY2/VQC0MyhYeKUFosQU6FxH2JmUe6VI=
@@ -56,8 +86,8 @@ github.com/gabriel-vasile/mimetype v1.4.9 h1:5k+WDwEsD9eTLL8Tz3L0VnmVh9QxGjRmjBv
 github.com/gabriel-vasile/mimetype v1.4.9/go.mod h1:WnSQhFKJuBlRyLiKohA/2DtIlPFAbguNaG7QCHcyGok=
 github.com/gin-contrib/sse v1.1.0 h1:n0w2GMuUpWDVp7qSpvze6fAu9iRxJY4Hmj6AmBOU05w=
 github.com/gin-contrib/sse v1.1.0/go.mod h1:hxRZ5gVpWMT7Z0B0gSNYqqsSCNIJMjzvm6fqCz9vjwM=
-github.com/gin-gonic/gin v1.10.0 h1:nTuyha1TYqgedzytsKYqna+DfLos46nTv2ygFy86HFU=
-github.com/gin-gonic/gin v1.10.0/go.mod h1:4PMNQiOhvDRa013RKVbsiNwoyezlm2rm0uX/T7kzp5Y=
+github.com/gin-gonic/gin v1.10.1 h1:T0ujvqyCSqRopADpgPgiTT63DUQVSfojyME59Ei63pQ=
+github.com/gin-gonic/gin v1.10.1/go.mod h1:4PMNQiOhvDRa013RKVbsiNwoyezlm2rm0uX/T7kzp5Y=
 github.com/gliderlabs/ssh v0.3.8 h1:a4YXD1V7xMF9g5nTkdfnja3Sxy1PVDCj1Zg4Wb8vY6c=
 github.com/gliderlabs/ssh v0.3.8/go.mod h1:xYoytBv1sV0aL3CavoDuJIQNURXkkfPA/wxQ1pL1fAU=
 github.com/go-git/gcfg v1.5.1-0.20230307220236-3a3c6141e376 h1:+zs/tPmkDkHx3U66DAb0lQFJrpS6731Oaa12ikc+DiI=
@@ -66,11 +96,11 @@ github.com/go-git/go-billy/v5 v5.6.2 h1:6Q86EsPXMa7c3YZ3aLAQsMA0VlWmy43r6FHqa/UN
 github.com/go-git/go-billy/v5 v5.6.2/go.mod h1:rcFC2rAsp/erv7CMz9GczHcuD0D32fWzH+MJAU+jaUU=
 github.com/go-git/go-git-fixtures/v4 v4.3.2-0.20231010084843-55a94097c399 h1:eMje31YglSBqCdIqdhKBW8lokaMrL3uTkpGYlE2OOT4=
 github.com/go-git/go-git-fixtures/v4 v4.3.2-0.20231010084843-55a94097c399/go.mod h1:1OCfN199q1Jm3HZlxleg+Dw/mwps2Wbk9frAWm+4FII=
-github.com/go-git/go-git/v5 v5.16.0 h1:k3kuOEpkc0DeY7xlL6NaaNg39xdgQbtH5mwCafHO9AQ=
-github.com/go-git/go-git/v5 v5.16.0/go.mod h1:4Ge4alE/5gPs30F2H1esi2gPd69R0C39lolkucHBOp8=
+github.com/go-git/go-git/v5 v5.16.2 h1:fT6ZIOjE5iEnkzKyxTHK1W4HGAsPhqEqiSAssSO77hM=
+github.com/go-git/go-git/v5 v5.16.2/go.mod h1:4Ge4alE/5gPs30F2H1esi2gPd69R0C39lolkucHBOp8=
 github.com/go-logr/logr v1.2.2/go.mod h1:jdQByPbusPIv2/zmleS9BjJVeZ6kBagPoEUsqbVz/1A=
-github.com/go-logr/logr v1.4.2 h1:6pFjapn8bFcIbiKo3XT4j/BhANplGihG6tvd+8rYgrY=
-github.com/go-logr/logr v1.4.2/go.mod h1:9T104GzyrTigFIr8wt5mBrctHMim0Nb2HLGrmQ40KvY=
+github.com/go-logr/logr v1.4.3 h1:CjnDlHq8ikf6E492q6eKboGOC0T8CDaOvkHCIg8idEI=
+github.com/go-logr/logr v1.4.3/go.mod h1:9T104GzyrTigFIr8wt5mBrctHMim0Nb2HLGrmQ40KvY=
 github.com/go-logr/stdr v1.2.2 h1:hSWxHoqTgW2S2qGc0LTAI563KZ5YKYRhT3MFKZMbjag=
 github.com/go-logr/stdr v1.2.2/go.mod h1:mMo/vtBO5dYbehREoey6XUKy/eSumjCCveDpRre4VKE=
 github.com/go-playground/assert/v2 v2.2.0 h1:JvknZsQTYeFEAhQwI4qEt9cyV5ONwRHC+lYKSsYSR8s=
@@ -93,8 +123,8 @@ github.com/golang/groupcache v0.0.0-20241129210726-2c02b8208cf8 h1:f+oWsMOmNPc8J
 github.com/golang/groupcache v0.0.0-20241129210726-2c02b8208cf8/go.mod h1:wcDNUvekVysuuOpQKo3191zZyTpiI6se1N1ULghS0sw=
 github.com/golang/protobuf v1.5.4 h1:i7eJL8qZTpSEXOPTxNKhASYpMn+8e5Q6AdndVa1dWek=
 github.com/golang/protobuf v1.5.4/go.mod h1:lnTiLA8Wa4RWRcIUkrtSVa5nRhsEGBg48fD6rSs7xps=
-github.com/google/generative-ai-go v0.19.0 h1:R71szggh8wHMCUlEMsW2A/3T+5LdEIkiaHSYgSpUgdg=
-github.com/google/generative-ai-go v0.19.0/go.mod h1:JYolL13VG7j79kM5BtHz4qwONHkeJQzOCkKXnpqtS/E=
+github.com/google/generative-ai-go v0.20.1 h1:6dEIujpgN2V0PgLhr6c/M1ynRdc7ARtiIDPFzj45uNQ=
+github.com/google/generative-ai-go v0.20.1/go.mod h1:TjOnZJmZKzarWbjUJgy+r3Ee7HGBRVLhOIgupnwR4Bg=
 github.com/google/go-cmp v0.6.0/go.mod h1:17dUlkBOakJ0+DkrSSNjCkIjxS6bF9zb3elmeNGIjoY=
 github.com/google/go-cmp v0.7.0 h1:wk8382ETsv4JYUZwIsn6YpYiWiBsYLSJiTsyBybVuN8=
 github.com/google/go-cmp v0.7.0/go.mod h1:pXiqmnSA92OHEEa9HXL2W4E7lf9JzCmGVUdgjX3N/iU=
@@ -105,8 +135,8 @@ github.com/google/uuid v1.6.0 h1:NIvaJDMOsjHA8n1jAhLSgzrAzy1Hgr+hNrb57e+94F0=
 github.com/google/uuid v1.6.0/go.mod h1:TIyPZe4MgqvfeYDBFedMoGGpEw/LqOeaOT+nhxU+yHo=
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@@ -138,10 +168,12 @@ github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd h1:TRLaZ9cD/w
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@@ -157,13 +189,13 @@ github.com/pmezard/go-difflib v1.0.0/go.mod h1:iKH77koFhYxTK1pcRnkKkqfTogsbg7gZN
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@@ -173,7 +205,6 @@ github.com/stretchr/objx v0.5.0/go.mod h1:Yh+to48EsGEfYuaHDzXPcE3xhTkx73EhmCGUpE
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@@ -192,29 +223,29 @@ github.com/tidwall/sjson v1.2.5 h1:kLy8mja+1c9jlljvWTlSazM7cKDRfJuR/bOJhcY5NcY=
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 golang.org/x/crypto v0.0.0-20210921155107-089bfa567519/go.mod h1:GvvjBRRGRdwPK5ydBHafDWAxML/pGHZbMvKqRZ5+Abc=
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@@ -222,8 +253,8 @@ golang.org/x/crypto v0.13.0/go.mod h1:y6Z2r+Rw4iayiXXAIxJIDAJ1zMW4yaTpebo8fPOliY
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 golang.org/x/exp v0.0.0-20250218142911-aa4b98e5adaa h1:t2QcU6V556bFjYgu4L6C+6VrCPyJZ+eyRsABUPs1mz4=
 golang.org/x/exp v0.0.0-20250218142911-aa4b98e5adaa/go.mod h1:BHOTPb3L19zxehTsLoJXVaTktb06DFgmdW6Wb9s8jqk=
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@@ -232,7 +263,6 @@ golang.org/x/mod v0.12.0/go.mod h1:iBbtSCu2XBx23ZKBPSOrRkjjQPZFPuis4dIYUhu/chs=
 golang.org/x/mod v0.15.0/go.mod h1:hTbmBsO62+eylJbnUtE2MGJUyE7QWk4xUqPFrRgJ+7c=
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 golang.org/x/net v0.0.0-20190620200207-3b0461eec859/go.mod h1:z5CRVTTTmAJ677TzLLGU+0bjPO0LkuOLi4/5GtJWs/s=
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 golang.org/x/net v0.0.0-20210226172049-e18ecbb05110/go.mod h1:m0MpNAwzfU5UDzcl9v0D8zg8gWTRqZa9RBIspLL5mdg=
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@@ -242,10 +272,10 @@ golang.org/x/net v0.15.0/go.mod h1:idbUs1IY1+zTqbi8yxTbhexhEEk5ur9LInksu6HrEpk=
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+golang.org/x/oauth2 v0.30.0/go.mod h1:B++QgG3ZKulg6sRPGD/mqlHQs5rB3Ml9erfeDY7xKlU=
 golang.org/x/sync v0.0.0-20190423024810-112230192c58/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
 golang.org/x/sync v0.0.0-20220722155255-886fb9371eb4/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
 golang.org/x/sync v0.1.0/go.mod h1:RxMgew5VJxzue5/jJTE5uejpjVlOe/izrB70Jof72aM=
@@ -253,8 +283,8 @@ golang.org/x/sync v0.3.0/go.mod h1:FU7BRWz2tNW+3quACPkgCx/L+uEAv1htQ0V83Z9Rj+Y=
 golang.org/x/sync v0.6.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
 golang.org/x/sync v0.7.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
 golang.org/x/sync v0.10.0/go.mod h1:Czt+wKu1gCyEFDUtn0jG5QVvpJ6rzVqr5aXyt9drQfk=
-golang.org/x/sync v0.13.0 h1:AauUjRAJ9OSnvULf/ARrrVywoJDy0YS2AwQ98I37610=
-golang.org/x/sync v0.13.0/go.mod h1:1dzgHSNfp02xaA81J2MS99Qcpr2w7fw1gpm99rleRqA=
+golang.org/x/sync v0.15.0 h1:KWH3jNZsfyT6xfAfKiz6MRNmd46ByHDYaZ7KSkCtdW8=
+golang.org/x/sync v0.15.0/go.mod h1:1dzgHSNfp02xaA81J2MS99Qcpr2w7fw1gpm99rleRqA=
 golang.org/x/sys v0.0.0-20190215142949-d0b11bdaac8a/go.mod h1:STP8DvDyc/dI5b8T5hshtkjS+E42TnysNCUPdjciGhY=
 golang.org/x/sys v0.0.0-20191026070338-33540a1f6037/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
 golang.org/x/sys v0.0.0-20201119102817-f84b799fce68/go.mod h1:h1NjWce9XRLGQEsW7wpKNCjG9DtNlClVuFLEZdDNbEs=
@@ -271,8 +301,8 @@ golang.org/x/sys v0.12.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg=
 golang.org/x/sys v0.17.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
 golang.org/x/sys v0.20.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
 golang.org/x/sys v0.28.0/go.mod h1:/VUhepiaJMQUp4+oa/7Zr1D23ma6VTLIYjOOTFZPUcA=
-golang.org/x/sys v0.32.0 h1:s77OFDvIQeibCmezSnk/q6iAfkdiQaJi4VzroCFrN20=
-golang.org/x/sys v0.32.0/go.mod h1:BJP2sWEmIv4KK5OTEluFJCKSidICx8ciO85XgH3Ak8k=
+golang.org/x/sys v0.33.0 h1:q3i8TbbEz+JRD9ywIRlyRAQbM0qF7hu24q3teo2hbuw=
+golang.org/x/sys v0.33.0/go.mod h1:BJP2sWEmIv4KK5OTEluFJCKSidICx8ciO85XgH3Ak8k=
 golang.org/x/telemetry v0.0.0-20240228155512-f48c80bd79b2/go.mod h1:TeRTkGYfJXctD9OcfyVLyj2J3IxLnKwHJR8f4D8a3YE=
 golang.org/x/term v0.0.0-20201126162022-7de9c90e9dd1/go.mod h1:bj7SfCRtBDWHUb9snDiAeCFNEtKQo2Wmx5Cou7ajbmo=
 golang.org/x/term v0.0.0-20210927222741-03fcf44c2211/go.mod h1:jbD1KX2456YbFQfuXm/mYQcufACuNUgVhRMnK/tPxf8=
@@ -282,8 +312,8 @@ golang.org/x/term v0.12.0/go.mod h1:owVbMEjm3cBLCHdkQu9b1opXd4ETQWc3BhuQGKgXgvU=
 golang.org/x/term v0.17.0/go.mod h1:lLRBjIVuehSbZlaOtGMbcMncT+aqLLLmKrsjNrUguwk=
 golang.org/x/term v0.20.0/go.mod h1:8UkIAJTvZgivsXaD6/pH6U9ecQzZ45awqEOzuCvwpFY=
 golang.org/x/term v0.27.0/go.mod h1:iMsnZpn0cago0GOrHO2+Y7u7JPn5AylBrcoWkElMTSM=
-golang.org/x/term v0.31.0 h1:erwDkOK1Msy6offm1mOgvspSkslFnIGsFnxOKoufg3o=
-golang.org/x/term v0.31.0/go.mod h1:R4BeIy7D95HzImkxGkTW1UQTtP54tio2RyHz7PwK0aw=
+golang.org/x/term v0.32.0 h1:DR4lr0TjUs3epypdhTOkMmuF5CDFJ/8pOnbzMZPQ7bg=
+golang.org/x/term v0.32.0/go.mod h1:uZG1FhGx848Sqfsq4/DlJr3xGGsYMu/L5GW4abiaEPQ=
 golang.org/x/text v0.3.0/go.mod h1:NqM8EUOU14njkJ3fqMW+pc6Ldnwhi/IjpwHt7yyuwOQ=
 golang.org/x/text v0.3.3/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
 golang.org/x/text v0.3.6/go.mod h1:5Zoc/QRtKVWzQhOtBMvqHzDpF6irO9z98xDceosuGiQ=
@@ -294,10 +324,10 @@ golang.org/x/text v0.13.0/go.mod h1:TvPlkZtksWOMsz7fbANvkp4WM8x/WCo/om8BMLbz+aE=
 golang.org/x/text v0.14.0/go.mod h1:18ZOQIKpY8NJVqYksKHtTdi31H5itFRjB5/qKTNYzSU=
 golang.org/x/text v0.15.0/go.mod h1:18ZOQIKpY8NJVqYksKHtTdi31H5itFRjB5/qKTNYzSU=
 golang.org/x/text v0.21.0/go.mod h1:4IBbMaMmOPCJ8SecivzSH54+73PCFmPWxNTLm+vZkEQ=
-golang.org/x/text v0.24.0 h1:dd5Bzh4yt5KYA8f9CJHCP4FB4D51c2c6JvN37xJJkJ0=
-golang.org/x/text v0.24.0/go.mod h1:L8rBsPeo2pSS+xqN0d5u2ikmjtmoJbDBT1b7nHvFCdU=
-golang.org/x/time v0.11.0 h1:/bpjEDfN9tkoN/ryeYHnv5hcMlc8ncjMcM4XBk5NWV0=
-golang.org/x/time v0.11.0/go.mod h1:CDIdPxbZBQxdj6cxyCIdrNogrJKMJ7pr37NYpMcMDSg=
+golang.org/x/text v0.26.0 h1:P42AVeLghgTYr4+xUnTRKDMqpar+PtX7KWuNQL21L8M=
+golang.org/x/text v0.26.0/go.mod h1:QK15LZJUUQVJxhz7wXgxSy/CJaTFjd0G+YLonydOVQA=
+golang.org/x/time v0.12.0 h1:ScB/8o8olJvc+CQPWrK3fPZNfh7qgwCrY0zJmoEQLSE=
+golang.org/x/time v0.12.0/go.mod h1:CDIdPxbZBQxdj6cxyCIdrNogrJKMJ7pr37NYpMcMDSg=
 golang.org/x/tools v0.0.0-20180917221912-90fa682c2a6e/go.mod h1:n7NCudcB/nEzxVGmLbDWY5pfWTLqBcC2KZ6jyYvM4mQ=
 golang.org/x/tools v0.0.0-20191119224855-298f0cb1881e/go.mod h1:b+2E5dAYhXwXZwtnZ6UAqBI28+e2cm9otk0dWdXHAEo=
 golang.org/x/tools v0.1.12/go.mod h1:hNGJHUnrk76NpqgfD5Aqm5Crs+Hm0VOH/i9J2+nxYbc=
@@ -305,14 +335,16 @@ golang.org/x/tools v0.6.0/go.mod h1:Xwgl3UAJ/d3gWutnCtw505GrjyAbvKui8lOU390QaIU=
 golang.org/x/tools v0.13.0/go.mod h1:HvlwmtVNQAhOuCjW7xxvovg8wbNq7LwfXh/k7wXUl58=
 golang.org/x/tools v0.21.1-0.20240508182429-e35e4ccd0d2d/go.mod h1:aiJjzUbINMkxbQROHiO6hDPo2LHcIPhhQsa9DLh0yGk=
 golang.org/x/xerrors v0.0.0-20190717185122-a985d3407aa7/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
-google.golang.org/api v0.230.0 h1:2u1hni3E+UXAXrONrrkfWpi/V6cyKVAbfGVeGtC3OxM=
-google.golang.org/api v0.230.0/go.mod h1:aqvtoMk7YkiXx+6U12arQFExiRV9D/ekvMCwCd/TksQ=
-google.golang.org/genproto/googleapis/api v0.0.0-20250422160041-2d3770c4ea7f h1:tjZsroqekhC63+WMqzmWyW5Twj/ZfR5HAlpd5YQ1Vs0=
-google.golang.org/genproto/googleapis/api v0.0.0-20250422160041-2d3770c4ea7f/go.mod h1:Cd8IzgPo5Akum2c9R6FsXNaZbH3Jpa2gpHlW89FqlyQ=
-google.golang.org/genproto/googleapis/rpc v0.0.0-20250422160041-2d3770c4ea7f h1:N/PrbTw4kdkqNRzVfWPrBekzLuarFREcbFOiOLkXon4=
-google.golang.org/genproto/googleapis/rpc v0.0.0-20250422160041-2d3770c4ea7f/go.mod h1:qQ0YXyHHx3XkvlzUtpXDkS29lDSafHMZBAZDc03LQ3A=
-google.golang.org/grpc v1.72.0 h1:S7UkcVa60b5AAQTaO6ZKamFp1zMZSU0fGDK2WZLbBnM=
-google.golang.org/grpc v1.72.0/go.mod h1:wH5Aktxcg25y1I3w7H69nHfXdOG3UiadoBtjh3izSDM=
+google.golang.org/api v0.236.0 h1:CAiEiDVtO4D/Qja2IA9VzlFrgPnK3XVMmRoJZlSWbc0=
+google.golang.org/api v0.236.0/go.mod h1:X1WF9CU2oTc+Jml1tiIxGmWFK/UZezdqEu09gcxZAj4=
+google.golang.org/genproto v0.0.0-20250505200425-f936aa4a68b2 h1:1tXaIXCracvtsRxSBsYDiSBN0cuJvM7QYW+MrpIRY78=
+google.golang.org/genproto v0.0.0-20250505200425-f936aa4a68b2/go.mod h1:49MsLSx0oWMOZqcpB3uL8ZOkAh1+TndpJ8ONoCBWiZk=
+google.golang.org/genproto/googleapis/api v0.0.0-20250603155806-513f23925822 h1:oWVWY3NzT7KJppx2UKhKmzPq4SRe0LdCijVRwvGeikY=
+google.golang.org/genproto/googleapis/api v0.0.0-20250603155806-513f23925822/go.mod h1:h3c4v36UTKzUiuaOKQ6gr3S+0hovBtUrXzTG/i3+XEc=
+google.golang.org/genproto/googleapis/rpc v0.0.0-20250603155806-513f23925822 h1:fc6jSaCT0vBduLYZHYrBBNY4dsWuvgyff9noRNDdBeE=
+google.golang.org/genproto/googleapis/rpc v0.0.0-20250603155806-513f23925822/go.mod h1:qQ0YXyHHx3XkvlzUtpXDkS29lDSafHMZBAZDc03LQ3A=
+google.golang.org/grpc v1.73.0 h1:VIWSmpI2MegBtTuFt5/JWy2oXxtjJ/e89Z70ImfD2ok=
+google.golang.org/grpc v1.73.0/go.mod h1:50sbHOUqWoCQGI8V2HQLJM0B+LMlIUjNSZmow7EVBQc=
 google.golang.org/protobuf v1.36.6 h1:z1NpPI8ku2WgiWnf+t9wTPsn6eP1L7ksHUlkfLvd9xY=
 google.golang.org/protobuf v1.36.6/go.mod h1:jduwjTPXsFjZGTmRluh+L6NjiWu7pchiJ2/5YcXBHnY=
 gopkg.in/check.v1 v0.0.0-20161208181325-20d25e280405/go.mod h1:Co6ibVJAznAaIkqp8huTwlJQCZ016jof/cbN4VW5Yz0=

nix/pkgs/fabric/default.nix

@@ -2,6 +2,7 @@
   lib,
   buildGoApplication,
   go,
+  installShellFiles,
 }:
 
 buildGoApplication {
@@ -20,6 +21,13 @@ buildGoApplication {
 
   inherit go;
 
+  nativeBuildInputs = [ installShellFiles ];
+  postInstall = ''
+    installShellCompletion --zsh ./completions/_fabric
+    installShellCompletion --bash ./completions/fabric.bash
+    installShellCompletion --fish ./completions/fabric.fish
+  '';
+
   meta = with lib; {
     description = "Fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere";
     homepage = "https://github.com/danielmiessler/fabric";

nix/pkgs/fabric/gomod2nix.toml

@@ -2,50 +2,95 @@ schema = 3
 
 [mod]
   [mod."cloud.google.com/go"]
-    version = "v0.120.1"
-    hash = "sha256-yWaLc06rGXk16K53rix8O4uPSX+AOZDgIpIXf+wlh10="
+    version = "v0.121.2"
+    hash = "sha256-BCgGHxKti8slH98UDDurtgzX3lgcYEklsmj4ImPpwlc="
   [mod."cloud.google.com/go/ai"]
-    version = "v0.10.2"
-    hash = "sha256-bsqvdylG8kk+AHtyvMRMv1TOjUmvONAgJ+14mKcwuzs="
+    version = "v0.12.1"
+    hash = "sha256-wg3oLMS68E/v7EdNzywbjwEmpk+u6U8LTnIc1pq8edo="
   [mod."cloud.google.com/go/auth"]
-    version = "v0.16.1"
-    hash = "sha256-rMPMNQh/YM/67b9Grfu0BFccWpS1SRhBepubQqXRAyg="
+    version = "v0.16.2"
+    hash = "sha256-BAU9WGFKe0pd5Eu3l/Mbts+QeCOjS+lChr5hrPBCzdA="
   [mod."cloud.google.com/go/auth/oauth2adapt"]
     version = "v0.2.8"
     hash = "sha256-GoXFqAbp1WO1tDj07PF5EyxDYvCBP0l0qwxY2oV2hfc="
   [mod."cloud.google.com/go/compute/metadata"]
-    version = "v0.6.0"
-    hash = "sha256-E8/cwio4xR8buCryR4HwR7+agb4M3zqgXSm7rBglmIY="
+    version = "v0.7.0"
+    hash = "sha256-jJZDW+hibqjMiY8OiJhgJALbGwEq+djLOxfYR7upQyE="
   [mod."cloud.google.com/go/longrunning"]
     version = "v0.6.7"
     hash = "sha256-9I0Nc2KWAEVoxDngNkqFUdASmZIAySfMEELlPh3Q3xA="
   [mod."dario.cat/mergo"]
-    version = "v1.0.1"
-    hash = "sha256-wcG6+x0k6KzOSlaPA+1RFxa06/RIAePJTAjjuhLbImw="
+    version = "v1.0.2"
+    hash = "sha256-p6jdiHlLEfZES8vJnDywG4aVzIe16p0CU6iglglIweA="
   [mod."github.com/Microsoft/go-winio"]
     version = "v0.6.2"
     hash = "sha256-tVNWDUMILZbJvarcl/E7tpSnkn7urqgSHa2Eaka5vSU="
   [mod."github.com/ProtonMail/go-crypto"]
-    version = "v1.2.0"
-    hash = "sha256-5fKgWUz6BoyFNNZ1OD9QjhBrhNEBCuVfO2WqH+X59oo="
-  [mod."github.com/anaskhan96/soup"]
-    version = "v1.2.5"
-    hash = "sha256-t8yCyK2y7x2qaI/3Yw16q3zVFqu+3acLcPgTr1MIKWg="
+    version = "v1.3.0"
+    hash = "sha256-TUG+C4MyeWglOmiwiW2/NUVurFHXLgEPRd3X9uQ1NGI="
   [mod."github.com/andybalholm/cascadia"]
     version = "v1.3.3"
     hash = "sha256-jv7ZshpSd7FZzKKN6hqlUgiR8C3y85zNIS/hq7g76Ho="
   [mod."github.com/anthropics/anthropic-sdk-go"]
-    version = "v0.2.0-beta.3"
-    hash = "sha256-QnR7MWiLPVii9jy7rjrZfg1UDgXCXkc2latdzFurrFM="
+    version = "v1.4.0"
+    hash = "sha256-4kwFw9gt/sRIlTo0fC2PbfLnCyc4lCOtmfQelhpORX8="
   [mod."github.com/araddon/dateparse"]
     version = "v0.0.0-20210429162001-6b43995a97de"
     hash = "sha256-UuX84naeRGMsFOgIgRoBHG5sNy1CzBkWPKmd6VbLwFw="
   [mod."github.com/atotto/clipboard"]
     version = "v0.1.4"
     hash = "sha256-ZZ7U5X0gWOu8zcjZcWbcpzGOGdycwq0TjTFh/eZHjXk="
+  [mod."github.com/aws/aws-sdk-go-v2"]
+    version = "v1.36.4"
+    hash = "sha256-Cpdphp8FQUbQlhAYvtPKDh1oZc84+/0bzLlx8CM1/BM="
+  [mod."github.com/aws/aws-sdk-go-v2/aws/protocol/eventstream"]
+    version = "v1.6.10"
+    hash = "sha256-9+ZMhWxtsm7ZtZCjBV5PZkOR5rt3bCOznuv45Iwf55c="
+  [mod."github.com/aws/aws-sdk-go-v2/config"]
+    version = "v1.27.27"
+    hash = "sha256-jQmc1lJmVeTezSeFs6KL2HAvCkP9ZWMdVbG5ymJQrKs="
+  [mod."github.com/aws/aws-sdk-go-v2/credentials"]
+    version = "v1.17.27"
+    hash = "sha256-7ITZjIF0ZmmCG3u5d88IfsAj0KF1IFm9KhWFlC6RtQo="
+  [mod."github.com/aws/aws-sdk-go-v2/feature/ec2/imds"]
+    version = "v1.16.11"
+    hash = "sha256-uedtRd/SIcFJlYZg1jtJdIJViZq1Poks9/J2Bm9/Ehw="
+  [mod."github.com/aws/aws-sdk-go-v2/internal/configsources"]
+    version = "v1.3.35"
+    hash = "sha256-AyQ+eJvyhahypIAqPScdkn44MYwBcr9iyrMC1BRSeZI="
+  [mod."github.com/aws/aws-sdk-go-v2/internal/endpoints/v2"]
+    version = "v2.6.35"
+    hash = "sha256-c8K+Nk5XrFMWaaxVsyhKgyJBZhs3Hkhjr/dIDXWZfSQ="
+  [mod."github.com/aws/aws-sdk-go-v2/internal/ini"]
+    version = "v1.8.0"
+    hash = "sha256-v76jTAr4rEgS5en49ikLh6nuvclN+VjpOPj83ZQ3sLo="
+  [mod."github.com/aws/aws-sdk-go-v2/service/bedrock"]
+    version = "v1.34.1"
+    hash = "sha256-OK7t+ieq4pviCnnhfSytANBF5Lwdz4KxjN10CC5pXyY="
+  [mod."github.com/aws/aws-sdk-go-v2/service/bedrockruntime"]
+    version = "v1.30.0"
+    hash = "sha256-MsEQfbqIREtMikRFqBpLCqdAC4gfgPSNbk08k5OJTbo="
+  [mod."github.com/aws/aws-sdk-go-v2/service/internal/accept-encoding"]
+    version = "v1.11.3"
+    hash = "sha256-TRhoRd7iY7K+pfdkSQLItyr52k2jO4TMYQ5vRGiOOMk="
+  [mod."github.com/aws/aws-sdk-go-v2/service/internal/presigned-url"]
+    version = "v1.11.17"
+    hash = "sha256-eUoYDAXcQNzCmwjXO9RWhrt0jGYlSjt2vQOlAlpIfoE="
+  [mod."github.com/aws/aws-sdk-go-v2/service/sso"]
+    version = "v1.22.4"
+    hash = "sha256-Q3tyDdJVq0BAstOYvCKPvNS4EHkhXt1pL/23KPQJMHM="
+  [mod."github.com/aws/aws-sdk-go-v2/service/ssooidc"]
+    version = "v1.26.4"
+    hash = "sha256-cPv6nmVPOjMUZjN2IeEiYQSzLeAOrfgGnSSvvhJ6iL4="
+  [mod."github.com/aws/aws-sdk-go-v2/service/sts"]
+    version = "v1.30.3"
+    hash = "sha256-4z/K4GPW9osiNM3SxFNZYsVPnSSU50Iuv29Sb2n4Fbk="
+  [mod."github.com/aws/smithy-go"]
+    version = "v1.22.2"
+    hash = "sha256-YdwVeW509cpqU357MjDM8ReL1vftkW8XIhSbJsbTh/s="
   [mod."github.com/bytedance/sonic"]
-    version = "v1.13.2"
-    hash = "sha256-IF2qmt4IxTwivMWHUJC8sg6d85/ORb2SWvJ54fvoAMI="
+    version = "v1.13.3"
+    hash = "sha256-Nnt5b2NkIvSXhGERQmyI0ka28hbWi7A7Zn3dsAjPcEA="
   [mod."github.com/bytedance/sonic/loader"]
     version = "v0.2.4"
     hash = "sha256-rv9LnePpm4OspSVbfSoVbohXzhu+dxE1BH1gm3mTmTc="
@@ -74,8 +119,8 @@ schema = 3
     version = "v1.1.0"
     hash = "sha256-2VP6zHEsPi0u2ZYpOTcLulwj1Gsmb6oA19qcP2/AzVM="
   [mod."github.com/gin-gonic/gin"]
-    version = "v1.10.0"
-    hash = "sha256-esJasHrJtuTBwGPGAoc/XSb428J8va+tPGcZ0gTfsgc="
+    version = "v1.10.1"
+    hash = "sha256-D98+chAdjb6JcLPkscOr8TgTW87UqA4h3cnY0XIr16c="
   [mod."github.com/go-git/gcfg"]
     version = "v1.5.1-0.20230307220236-3a3c6141e376"
     hash = "sha256-f4k0gSYuo0/q3WOoTxl2eFaj7WZpdz29ih6CKc8Ude8="
@@ -83,11 +128,11 @@ schema = 3
     version = "v5.6.2"
     hash = "sha256-VgbxcLkHjiSyRIfKS7E9Sn8OynCrMGUDkwFz6K2TVL4="
   [mod."github.com/go-git/go-git/v5"]
-    version = "v5.16.0"
-    hash = "sha256-01obPHvt1PG3r8XH8TgnNfcOhaYwWEkJ0TR5QGdZqmE="
+    version = "v5.16.2"
+    hash = "sha256-KdOf4KwJAJUIB/EcQH6wc7jpcABCISWur3vOTpAo+/c="
   [mod."github.com/go-logr/logr"]
-    version = "v1.4.2"
-    hash = "sha256-/W6qGilFlZNTb9Uq48xGZ4IbsVeSwJiAMLw4wiNYHLI="
+    version = "v1.4.3"
+    hash = "sha256-Nnp/dEVNMxLp3RSPDHZzGbI8BkSNuZMX0I0cjWKXXLA="
   [mod."github.com/go-logr/stdr"]
     version = "v1.2.2"
     hash = "sha256-rRweAP7XIb4egtT1f2gkz4sYOu7LDHmcJ5iNsJUd0sE="
@@ -116,8 +161,8 @@ schema = 3
     version = "v0.0.0-20241129210726-2c02b8208cf8"
     hash = "sha256-AdLZ3dJLe/yduoNvZiXugZxNfmwJjNQyQGsIdzYzH74="
   [mod."github.com/google/generative-ai-go"]
-    version = "v0.19.0"
-    hash = "sha256-x2K1nkRwtne9MeP5B8FpwavYqQx564go5LzmcBJ0KT4="
+    version = "v0.20.1"
+    hash = "sha256-9bSpEs4kByhgyTKiHdOY5muYjGBTluA1LvEjw2gSoLI="
   [mod."github.com/google/s2a-go"]
     version = "v0.1.9"
     hash = "sha256-0AdSpSTso4bATmM/9qamWzKrVtOLDf7afvDhoiT/UpA="
@@ -128,8 +173,8 @@ schema = 3
     version = "v0.3.6"
     hash = "sha256-hPMF0s+X4/ul98GvVuw/ZNOupEXhIDB1yvWymZWYEbU="
   [mod."github.com/googleapis/gax-go/v2"]
-    version = "v2.14.1"
-    hash = "sha256-iRS/KsAVTePrvTlwA7vKcQnwY6Jz329WdgzFw0hF8wk="
+    version = "v2.14.2"
+    hash = "sha256-QyY7wuCkrOJCJIf9Q884KD/BC3vk/QtQLXeLeNPt750="
   [mod."github.com/jbenet/go-context"]
     version = "v0.0.0-20150711004518-d14ea06fba99"
     hash = "sha256-VANNCWNNpARH/ILQV9sCQsBWgyL2iFT+4AHZREpxIWE="
@@ -161,8 +206,11 @@ schema = 3
     version = "v1.0.2"
     hash = "sha256-+W9EIW7okXIXjWEgOaMh58eLvBZ7OshW2EhaIpNLSBU="
   [mod."github.com/ollama/ollama"]
-    version = "v0.6.6"
-    hash = "sha256-a2Be14e+pcJo15fM/+0ksE9HVl8I4hW6ujqbpNh9bpA="
+    version = "v0.9.0"
+    hash = "sha256-r2eU+kMG3tuJy2B43RXsfmeltzM9t05NEmNiJAW5qr4="
+  [mod."github.com/openai/openai-go"]
+    version = "v1.8.2"
+    hash = "sha256-O8aV3zEj6o8kIlzlkYaTW4RzvwR3qNUBYiN8SuTM1R0="
   [mod."github.com/otiai10/copy"]
     version = "v1.14.1"
     hash = "sha256-8RR7u17SbYg9AeBXVHIv5ZMU+kHmOcx0rLUKyz6YtU0="
@@ -182,14 +230,14 @@ schema = 3
     version = "v1.0.0"
     hash = "sha256-/FtmHnaGjdvEIKAJtrUfEhV7EVo5A/eYrtdnUkuxLDA="
   [mod."github.com/samber/lo"]
-    version = "v1.49.1"
-    hash = "sha256-xMQS9Sx2Bpvwo/9JvSVkJ4RXYOSHm642WRqWA6y0AnU="
-  [mod."github.com/sashabaranov/go-openai"]
-    version = "v1.38.2"
-    hash = "sha256-AnBycaxufzWlLS1YBq7MiHDED+Jqtu9oAySKcoL4HOA="
+    version = "v1.50.0"
+    hash = "sha256-KDFks82BKu39sGt0f972IyOkohV2U0r1YvsnlNLdugY="
   [mod."github.com/sergi/go-diff"]
-    version = "v1.3.2-0.20230802210424-5b0b94c5c0d3"
-    hash = "sha256-UcLU83CPMbSoKI8RLvLJ7nvGaE2xRSL1RjoHCVkMzUM="
+    version = "v1.4.0"
+    hash = "sha256-rs9NKpv/qcQEMRg7CmxGdP4HGuFdBxlpWf9LbA9wS4k="
+  [mod."github.com/sgaunet/perplexity-go/v2"]
+    version = "v2.8.0"
+    hash = "sha256-w1S14Jf4/6LFODREmmiJvPtkZh4Sor81Rr1PqC5pIak="
   [mod."github.com/skeema/knownhosts"]
     version = "v1.3.1"
     hash = "sha256-kjqQDzuncQNTuOYegqVZExwuOt/Z73m2ST7NZFEKixI="
@@ -212,8 +260,8 @@ schema = 3
     version = "v0.15.1"
     hash = "sha256-HLk6oUe7EoITrNvP0y8D6BtIgIcmDZYtb/xl/dufIoY="
   [mod."github.com/ugorji/go/codec"]
-    version = "v1.2.12"
-    hash = "sha256-sp1LJ93UK7mFwgZqG8jxCgTCPgKR74HNU6XxX0Jfjm0="
+    version = "v1.2.14"
+    hash = "sha256-PoVXlCBE8SvMWpXx9FRsQOSAmE/+5SnPGr4m5BGoyIo="
   [mod."github.com/xanzy/ssh-agent"]
     version = "v0.3.3"
     hash = "sha256-l3pGB6IdzcPA/HLk93sSN6NM2pKPy+bVOoacR5RC2+c="
@@ -221,56 +269,56 @@ schema = 3
     version = "v1.1.0"
     hash = "sha256-cA9qCCu8P1NSJRxgmpfkfa5rKyn9X+Y/9FSmSd5xjyo="
   [mod."go.opentelemetry.io/contrib/instrumentation/google.golang.org/grpc/otelgrpc"]
-    version = "v0.60.0"
-    hash = "sha256-DkIpL4xUy+UIQBUK6VgbsI79TbZUltaIhXl4UJWym6E="
+    version = "v0.61.0"
+    hash = "sha256-o5w9k3VbqP3gaXI3Aelw93LLHH53U4PnkYVwc3MaY3Y="
   [mod."go.opentelemetry.io/contrib/instrumentation/net/http/otelhttp"]
-    version = "v0.60.0"
-    hash = "sha256-twGSnNbXzcw5qvRiFc/zz5rS+nhmbgSVPcd5jrZjlDg="
+    version = "v0.61.0"
+    hash = "sha256-4pfXD7ErXhexSynXiEEQSAkWoPwHd7PEDE3M1Zi5gLM="
   [mod."go.opentelemetry.io/otel"]
-    version = "v1.35.0"
-    hash = "sha256-LHrBtBnyDtvJGtrXHMPIFe7U53B4bZzpePB4u8Xo4Bg="
+    version = "v1.36.0"
+    hash = "sha256-j8wojdCtKal3LKojanHA8KXXQ0FkbWONpO8tUxpJDko="
   [mod."go.opentelemetry.io/otel/metric"]
-    version = "v1.35.0"
-    hash = "sha256-K9I0LRZqSLrC09Cuk7tp0VEk3cUVDs8S5MGnu9jw92Q="
+    version = "v1.36.0"
+    hash = "sha256-z6Uqi4HhUljWIYd58svKK5MqcGbpcac+/M8JeTrUtJ8="
   [mod."go.opentelemetry.io/otel/trace"]
-    version = "v1.35.0"
-    hash = "sha256-HC2+OGDe2rg0+E8WymQbUNoc249NXM1gIBJzK4UhcQE="
+    version = "v1.36.0"
+    hash = "sha256-owWD9x1lp8aIJqYt058BXPUsIMHdk3RI0escso0BxwA="
   [mod."golang.org/x/arch"]
-    version = "v0.16.0"
-    hash = "sha256-+DMOuIw9GVyhM4VHdYCZepTU/EEHqDfrxJ2F83TOs5k="
+    version = "v0.18.0"
+    hash = "sha256-tUpUPERjmRi7zldj0oPlnbnBhEkcI9iQGvP1HqlsK10="
   [mod."golang.org/x/crypto"]
-    version = "v0.37.0"
-    hash = "sha256-9NwDEcii1e2JYM/+3y1yNzWnt/ChMm27e9OtfuF39OM="
-  [mod."golang.org/x/net"]
     version = "v0.39.0"
-    hash = "sha256-IP29+yGphWKUT7wHTyzqA2rnRT4AJ7oWcT6NKLzkWcM="
+    hash = "sha256-FtwjbVoAhZkx7F2hmzi9Y0J87CVVhWcrZzun+zWQLzc="
+  [mod."golang.org/x/net"]
+    version = "v0.41.0"
+    hash = "sha256-6/pi8rNmGvBFzkJQXkXkMfL1Bjydhg3BgAMYDyQ/Uvg="
   [mod."golang.org/x/oauth2"]
-    version = "v0.29.0"
-    hash = "sha256-IzAypzW8cN5ZbQiIdMTcTiVuUNpMSkwuxeFrJZxcDl8="
+    version = "v0.30.0"
+    hash = "sha256-btD7BUtQpOswusZY5qIU90uDo38buVrQ0tmmQ8qNHDg="
   [mod."golang.org/x/sync"]
-    version = "v0.13.0"
-    hash = "sha256-CElRNe74Or/ysUkb/m3Wcz/juO/tB5fhQbAaxA5AizY="
+    version = "v0.15.0"
+    hash = "sha256-Jf4ehm8H8YAWY6mM151RI5CbG7JcOFtmN0AZx4bE3UE="
   [mod."golang.org/x/sys"]
-    version = "v0.32.0"
-    hash = "sha256-c9RRnyKQy9Kl8hpbtcgkm1O5H7gOdk9Rv925F8fZS6E="
+    version = "v0.33.0"
+    hash = "sha256-wlOzIOUgAiGAtdzhW/KPl/yUVSH/lvFZfs5XOuJ9LOQ="
   [mod."golang.org/x/text"]
-    version = "v0.24.0"
-    hash = "sha256-qFbmteGOvJfvbLXiOSI8Fsz5Ixt2ZhSYx0/sIqApC7Y="
+    version = "v0.26.0"
+    hash = "sha256-N+27nBCyGvje0yCTlUzZoVZ0LRxx4AJ+eBlrFQVRlFQ="
   [mod."golang.org/x/time"]
-    version = "v0.11.0"
-    hash = "sha256-ImTej/e5iUHbWPZMA4M2GYbsbiiZQxIrgcnYsc7uD68="
+    version = "v0.12.0"
+    hash = "sha256-Cp3oxrCMH2wyxjzr5SHVmyhgaoUuSl56Uy00Q7DYEpw="
   [mod."google.golang.org/api"]
-    version = "v0.230.0"
-    hash = "sha256-ihEdZnRbQdwpbgj9AZEZLNY14FqHmacFGFocOqExSVY="
+    version = "v0.236.0"
+    hash = "sha256-tP1RSUSnQ4a0axgZQwEZgKF1E13nL02FSP1NPSZr0Rc="
   [mod."google.golang.org/genproto/googleapis/api"]
-    version = "v0.0.0-20250422160041-2d3770c4ea7f"
-    hash = "sha256-Y4wbEHh9Un0QKplTl2S5lhWDUha9QThx5DhWJbDG9fo="
+    version = "v0.0.0-20250603155806-513f23925822"
+    hash = "sha256-0CS432v9zVhkVLqFpZtxBX8rvVqP67lb7qQ3es7RqIU="
   [mod."google.golang.org/genproto/googleapis/rpc"]
-    version = "v0.0.0-20250422160041-2d3770c4ea7f"
+    version = "v0.0.0-20250603155806-513f23925822"
     hash = "sha256-WK7iDtAhH19NPe3TywTQlGjDawNaDKWnxhFL9PgVUwM="
   [mod."google.golang.org/grpc"]
-    version = "v1.72.0"
-    hash = "sha256-tqu+ACMfKjhqdCGN3jLEmtaHB5ywgHGaS/eDeDRnf+M="
+    version = "v1.73.0"
+    hash = "sha256-LfVlwip++q2DX70RU6CxoXglx1+r5l48DwlFD05G11c="
   [mod."google.golang.org/protobuf"]
     version = "v1.36.6"
     hash = "sha256-lT5qnefI5FDJnowz9PEkAGylH3+fE+A3DJDkAyy9RMc="

nix/pkgs/fabric/version.nix

@@ -1 +1 @@
-"1.4.183"
+"1.4.222"

patterns/analyze_debate/system.md

@@ -22,19 +22,20 @@ Take a deep breath and think step by step about how to best accomplish this goal
     This must be under the heading "INSIGHTFULNESS SCORE (0 = not very interesting and insightful to 10 = very interesting and insightful)".
     - A rating of how emotional the debate was from 0 (very calm) to 5 (very emotional). This must be under the heading "EMOTIONALITY SCORE (0 (very calm) to 5 (very emotional))".
     - A list of the participants of the debate and a score of their emotionality from 0 (very calm) to 5 (very emotional). This must be under the heading "PARTICIPANTS".
-    - A list of arguments attributed to participants with names and quotes. If possible, this should include external references that disprove or back up their claims. 
+    - A list of arguments attributed to participants with names and quotes. Each argument summary must be EXACTLY 16 words. If possible, this should include external references that disprove or back up their claims. 
     It is IMPORTANT that these references are from trusted and verifiable sources that can be easily accessed. These sources have to BE REAL and NOT MADE UP. This must be under the heading "ARGUMENTS". 
     If possible, provide an objective assessment of the truth of these arguments. If you assess the truth of the argument, provide some sources that back up your assessment. The material you provide should be from reliable, verifiable, and trustworthy sources. DO NOT MAKE UP SOURCES.
-    - A list of agreements the participants have reached, attributed with names and quotes. This must be under the heading "AGREEMENTS".
-    - A list of disagreements the participants were unable to resolve and the reasons why they remained unresolved, attributed with names and quotes. This must be under the heading "DISAGREEMENTS".
-    - A list of possible misunderstandings and why they may have occurred, attributed with names and quotes. This must be under the heading "POSSIBLE MISUNDERSTANDINGS".
-    - A list of learnings from the debate. This must be under the heading "LEARNINGS".
-    - A list of takeaways that highlight ideas to think about, sources to explore, and actionable items. This must be under the heading "TAKEAWAYS".
+    - A list of agreements the participants have reached. Each agreement summary must be EXACTLY 16 words, followed by names and quotes. This must be under the heading "AGREEMENTS".
+    - A list of disagreements the participants were unable to resolve. Each disagreement summary must be EXACTLY 16 words, followed by names and quotes explaining why they remained unresolved. This must be under the heading "DISAGREEMENTS".
+    - A list of possible misunderstandings. Each misunderstanding summary must be EXACTLY 16 words, followed by names and quotes explaining why they may have occurred. This must be under the heading "POSSIBLE MISUNDERSTANDINGS".
+    - A list of learnings from the debate. Each learning must be EXACTLY 16 words. This must be under the heading "LEARNINGS".
+    - A list of takeaways that highlight ideas to think about, sources to explore, and actionable items. Each takeaway must be EXACTLY 16 words. This must be under the heading "TAKEAWAYS".
 
 # OUTPUT INSTRUCTIONS
 
 - Output all sections above.
-- Use Markdown to structure your output.
+- Do not use any markdown formatting (no asterisks, no bullet points, no headers).
+- Keep all agreements, arguments, recommendations, learnings, and takeaways to EXACTLY 16 words each.
 - When providing quotes, these quotes should clearly express the points you are using them for. If necessary, use multiple quotes.
 
 # INPUT:

patterns/analyze_paper/system.md

@@ -8,19 +8,19 @@ Take a deep breath and think step by step about how to best accomplish this goal
 
 - Consume the entire paper and think deeply about it.
 
-- Map out all the claims and implications on a virtual whiteboard in your mind.
+- Map out all the claims and implications on a giant virtual whiteboard in your mind.
 
 # OUTPUT 
 
-- Extract a summary of the paper and its conclusions into a 25-word sentence called SUMMARY.
+- Extract a summary of the paper and its conclusions into a 16-word sentence called SUMMARY.
 
 - Extract the list of authors in a section called AUTHORS.
 
 - Extract the list of organizations the authors are associated, e.g., which university they're at, with in a section called AUTHOR ORGANIZATIONS.
 
-- Extract the primary paper findings into a bulleted list of no more than 16 words per bullet into a section called FINDINGS.
+- Extract the most surprising and interesting paper findings into a 10 bullets of no more than 16 words per bullet into a section called FINDINGS.
 
-- Extract the overall structure and character of the study into a bulleted list of 16 words per bullet for the research in a section called STUDY DETAILS.
+- Extract the overall structure and character of the study into a bulleted list of 16 words per bullet for the research in a section called STUDY OVERVIEW.
 
 - Extract the study quality by evaluating the following items in a section called STUDY QUALITY that has the following bulleted sub-sections:
 
@@ -76,7 +76,9 @@ END EXAMPLE CHART
 
 - SUMMARY STATEMENT:
 
-A final 25-word summary of the paper, its findings, and what we should do about it if it's true.
+A final 16-word summary of the paper, its findings, and what we should do about it if it's true.
+
+Also add 5 8-word bullets of how you got to that rating and conclusion / summary.
 
 # RATING NOTES
 
@@ -84,21 +86,23 @@ A final 25-word summary of the paper, its findings, and what we should do about
 
 - An A would be a paper that is novel, rigorous, empirical, and has no conflicts of interest.
 
-- A paper could get an A if it's theoretical but everything else would have to be perfect.
+- A paper could get an A if it's theoretical but everything else would have to be VERY good.
 
 - The stronger the claims the stronger the evidence needs to be, as well as the transparency into the methodology. If the paper makes strong claims, but the evidence or transparency is weak, then the RIGOR score should be lowered.
 
 - Remove at least 1 grade (and up to 2) for papers where compelling data is provided but it's not clear what exact tests were run and/or how to reproduce those tests. 
 
-- Do not relax this transparency requirement for papers that claim security reasons.
-
-- If a paper does not clearly articulate its methodology in a way that's replicable, lower the RIGOR and overall score significantly.
+- Do not relax this transparency requirement for papers that claim security reasons. If they didn't show their work we have to assume the worst given the reproducibility crisis..
 
 - Remove up to 1-3 grades for potential conflicts of interest indicated in the report.
 
+# ANALYSIS INSTRUCTIONS
+
+- Tend towards being more critical. Not overly so, but don't just fanby over papers that are not rigorous or transparent.
+ 
 # OUTPUT INSTRUCTIONS
 
-- Output all sections above.
+- After deeply considering all the sections above and how they interact with each other, output all sections above.
 
 - Ensure the scoring looks closely at the reproducibility and transparency of the methodology, and that it doesn't give a pass to papers that don't provide the data or methodology for safety or other reasons.
 
@@ -108,7 +112,7 @@ Known         [-2--------]    Novel
 Weak          [-------8--]    Rigorous
 Theoretical   [--3-------]     Empirical
 
-- For the findings and other analysis sections, write at the 9th-grade reading level. This means using short sentences and simple words/concepts to explain everything.
+- For the findings and other analysis sections, and in fact all writing, write in the clear, approachable style of Paul Graham.
 
 - Ensure there's a blank line between each bullet of output.
 
@@ -120,4 +124,3 @@ Theoretical   [--3-------]     Empirical
 
 # INPUT:
 
-INPUT:

patterns/analyze_paper_simple/system.md

@@ -0,0 +1,122 @@
+# IDENTITY and PURPOSE
+
+You are a research paper analysis service focused on determining the primary findings of the paper and analyzing its scientific rigor and quality.
+
+Take a deep breath and think step by step about how to best accomplish this goal using the following steps.
+
+# STEPS
+
+- Consume the entire paper and think deeply about it.
+
+- Map out all the claims and implications on a virtual whiteboard in your mind.
+
+# FACTORS TO CONSIDER
+
+- Extract a summary of the paper and its conclusions into a 25-word sentence called SUMMARY.
+
+- Extract the list of authors in a section called AUTHORS.
+
+- Extract the list of organizations the authors are associated, e.g., which university they're at, with in a section called AUTHOR ORGANIZATIONS.
+
+- Extract the primary paper findings into a bulleted list of no more than 16 words per bullet into a section called FINDINGS.
+
+- Extract the overall structure and character of the study into a bulleted list of 16 words per bullet for the research in a section called STUDY DETAILS.
+
+- Extract the study quality by evaluating the following items in a section called STUDY QUALITY that has the following bulleted sub-sections:
+
+- STUDY DESIGN: (give a 15 word description, including the pertinent data and statistics.)
+
+- SAMPLE SIZE: (give a 15 word description, including the pertinent data and statistics.)
+
+- CONFIDENCE INTERVALS (give a 15 word description, including the pertinent data and statistics.)
+
+- P-VALUE (give a 15 word description, including the pertinent data and statistics.)
+
+- EFFECT SIZE (give a 15 word description, including the pertinent data and statistics.)
+
+- CONSISTENCE OF RESULTS (give a 15 word description, including the pertinent data and statistics.)
+
+- METHODOLOGY TRANSPARENCY (give a 15 word description of the methodology quality and documentation.)
+
+- STUDY REPRODUCIBILITY (give a 15 word description, including how to fully reproduce the study.)
+
+- Data Analysis Method (give a 15 word description, including the pertinent data and statistics.)
+
+- Discuss any Conflicts of Interest in a section called CONFLICTS OF INTEREST. Rate the conflicts of interest as NONE DETECTED, LOW, MEDIUM, HIGH, or CRITICAL.
+
+- Extract the researcher's analysis and interpretation in a section called RESEARCHER'S INTERPRETATION, in a 15-word sentence.
+
+- In a section called PAPER QUALITY output the following sections:
+
+- Novelty: 1 - 10 Rating, followed by a 15 word explanation for the rating.
+
+- Rigor: 1 - 10 Rating, followed by a 15 word explanation for the rating.
+
+- Empiricism: 1 - 10 Rating, followed by a 15 word explanation for the rating.
+
+- Rating Chart: Create a chart like the one below that shows how the paper rates on all these dimensions. 
+
+- Known to Novel is how new and interesting and surprising the paper is on a scale of 1 - 10.
+
+- Weak to Rigorous is how well the paper is supported by careful science, transparency, and methodology on a scale of 1 - 10.
+
+- Theoretical to Empirical is how much the paper is based on purely speculative or theoretical ideas or actual data on a scale of 1 - 10. Note: Theoretical papers can still be rigorous and novel and should not be penalized overall for being Theoretical alone.
+
+EXAMPLE CHART for 7, 5, 9 SCORES (fill in the actual scores):
+
+Known         [------7---]    Novel
+Weak          [----5-----]    Rigorous
+Theoretical   [--------9-]     Empirical
+
+END EXAMPLE CHART
+
+- FINAL SCORE:
+
+- A - F based on the scores above, conflicts of interest, and the overall quality of the paper. On a separate line, give a 15-word explanation for the grade.
+
+- SUMMARY STATEMENT:
+
+A final 25-word summary of the paper, its findings, and what we should do about it if it's true.
+
+# RATING NOTES
+
+- If the paper makes claims and presents stats but doesn't show how it arrived at these stats, then the Methodology Transparency would be low, and the RIGOR score should be lowered as well.
+
+- An A would be a paper that is novel, rigorous, empirical, and has no conflicts of interest.
+
+- A paper could get an A if it's theoretical but everything else would have to be perfect.
+
+- The stronger the claims the stronger the evidence needs to be, as well as the transparency into the methodology. If the paper makes strong claims, but the evidence or transparency is weak, then the RIGOR score should be lowered.
+
+- Remove at least 1 grade (and up to 2) for papers where compelling data is provided but it's not clear what exact tests were run and/or how to reproduce those tests. 
+
+- Do not relax this transparency requirement for papers that claim security reasons.
+
+- If a paper does not clearly articulate its methodology in a way that's replicable, lower the RIGOR and overall score significantly.
+
+- Remove up to 1-3 grades for potential conflicts of interest indicated in the report.
+
+- Ensure the scoring looks closely at the reproducibility and transparency of the methodology, and that it doesn't give a pass to papers that don't provide the data or methodology for safety or other reasons.
+
+# OUTPUT INSTRUCTIONS
+
+Output only the following—not all the sections above.
+
+Use Markdown bullets with dashes for the output (no bold or italics (asterisks)).
+
+- The Title of the Paper, starting with the word TITLE:
+- A 16-word sentence summarizing the paper's main claim, in the style of Paul Graham, starting with the word SUMMARY: which is not part of the 16 words.
+- A 32-word summary of the implications stated or implied by the paper, in the style of Paul Graham, starting with the word IMPLICATIONS: which is not part of the 32 words.
+- A 32-word summary of the primary recommendation stated or implied by the paper, in the style of Paul Graham, starting with the word RECOMMENDATION: which is not part of the 32 words.
+- A 32-word bullet covering the authors of the paper and where they're out of, in the style of Paul Graham, starting with the word AUTHORS: which is not part of the 32 words.
+- A 32-word bullet covering the methodology, including the type of research, how many studies it looked at, how many experiments, the p-value, etc. In other words the various aspects of the research that tell us the amount and type of rigor that went into the paper, in the style of Paul Graham, starting with the word METHODOLOGY: which is not part of the 32 words.
+- A 32-word bullet covering any potential conflicts or bias that can logically be inferred by the authors, their affiliations, the methodology, or any other related information in the paper, in the style of Paul Graham, starting with the word CONFLICT/BIAS: which is not part of the 32 words.
+- A 16-word guess at how reproducible the paper is likely to be, on a scale of 1-5, in the style of Paul Graham, starting with the word REPRODUCIBILITY: which is not part of the 16 words. Output the score as n/5, not spelled out. Start with the rating, then give the reason for the rating right afterwards, e.g.: "2/5 — The paper ...".
+
+- In the markdown, don't use formatting like bold or italics. Make the output maximally readable in plain text.
+
+- Do not output warnings or notes—just output the requested sections.
+
+# INPUT:
+
+INPUT:

patterns/analyze_terraform_plan/system.md

@@ -0,0 +1,24 @@
+# IDENTITY and PURPOSE
+
+You are an expert Terraform plan analyser. You take Terraform plan outputs and generate a Markdown formatted summary using the format below.
+
+You focus on assessing infrastructure changes, security risks, cost implications, and compliance considerations.
+
+## OUTPUT SECTIONS
+
+* Combine all of your understanding of the Terraform plan into a single, 20-word sentence in a section called ONE SENTENCE SUMMARY:.
+* Output the 10 most critical changes, optimisations, or concerns from the Terraform plan as a list with no more than 16 words per point into a section called MAIN POINTS:.
+* Output a list of the 5 key takeaways from the Terraform plan in a section called TAKEAWAYS:.
+
+## OUTPUT INSTRUCTIONS
+
+* Create the output using the formatting above.
+* You only output human-readable Markdown.
+* Output numbered lists, not bullets.
+* Do not output warnings or notes—just the requested sections.
+* Do not repeat items in the output sections.
+* Do not start items with the same opening words.
+
+## INPUT
+
+INPUT:

patterns/create_hormozi_offer/system.md

@@ -16,349 +16,279 @@ The goal of this exercise are to:
 
 CONTENT SUMMARY
 
-$100M Offers by Alex Hormozi 
-$100M Offers, Alex Hormozi shows you “how to make offers so good people will
-Introduction
-In his book, feel stupid saying no.
-” The offer is “the starting point of any conversation to initiate a
-transaction with a customer.”
-Alex Hormozi shows you how to make profitable offers by “reliably turning advertising dollars
-into (enormous) profits using a combination of pricing, value, guarantees, and naming
-strategies.” Combining these factors in the right amounts will result in a Grand Slam Offer. “The
-good news is that in business, you only need to hit one Grand Slam Offer to retire forever.”
+Introduction: $100M Offers
+
+In his book, Alex Hormozi shows you “how to make offers so good people feel stupid saying no."
+The offer is “the starting point of any conversation to initiate a transaction with a customer.”
+Alex Hormozi shows you how to make profitable offers by “reliably turning advertising dollars into (enormous) profits using a combination of pricing, value, guarantees, and naming strategies.” Combining these factors in the right amounts will result in a Grand Slam Offer. “The good news is that in business, you only need to hit one Grand Slam Offer to retire forever.”
+
 Section I: How We Got Here
-In Section I of $100M Offers, Alex Hormozi introduces his personal story from debt to success
-along with the concept of the “Grand Slam Offer.”
+
+In Section I of $100M Offers, Alex Hormozi introduces his personal story from debt to success along with the concept of the “Grand Slam Offer.”
+
 Chapter 1. How We Got Here
-Alex Hormozi begins with his story from Christmas Eve in 2016. He was on the verge of going
-broke. But a few days later, he hit a grand slam in early January of 2017. In $100M Offers, Alex
-Hormozi shares this vital skill of making offers, as it was life-changing for him, and he wants to
-deliver for you.
+
+Alex Hormozi begins with his story from Christmas Eve in 2016. He was on the verge of going broke. But a few days later, he hit a grand slam in early January of 2017. In $100M Offers, Alex Hormozi shares this vital skill of making offers, as it was life-changing for him, and he wants to deliver for you.
+
 Chapter 2. Grand Slam Offers
-In Chapter 2 of $100M Offers, Alex Hormozi introduces the concept of the “Grand Slam Offer.”
-Travis Jones states that the secret to sales is to “Make people an offer so good they would feel
-stupid saying no.” Further, to have a business, we need to make our prospects an offer:
-Offer – “the goods and services you agree to provide, how you accept payment, and the terms
-of the agreement”
-Offers start the process of customer acquisition and earning money, and they can range from
-nothing to a grand slam:
-• No offer? No business. No life.
-• Bad offer? Negative profit. No business. Miserable life.
-• Decent offer? No profit. Stagnating business. Stagnating life.
-• Good offer? Some profit. Okay business. Okay life.
-• Grand Slam Offer? Fantastic profit. Insane business. Freedom.
+
+In Chapter 2 of $100M Offers, Alex Hormozi introduces the concept of the “Grand Slam Offer.” Travis Jones states that the secret to sales is to “Make people an offer so good they would feel stupid saying no.” Further, to have a business, we need to make our prospects an offer:
+Offer – “the goods and services you agree to provide, how you accept payment, and the terms of the agreement”
+Offers start the process of customer acquisition and earning money, and they can range from nothing to a grand slam:
+- No offer? No business. No life.
+- Bad offer? Negative profit. No business. Miserable life.
+- Decent offer? No profit. Stagnating business. Stagnating life.
+- Good offer? Some profit. Okay business. Okay life.
+- Grand Slam Offer? Fantastic profit. Insane business. Freedom.
+
 There are two significant issues that most entrepreneurs face:
 1. Not Enough Clients
 2. Not Enough Cash or excess profit at the end of the month
-$100M Offers by Alex Hormozi | 
+
 Section II: Pricing
+
 In Section II of $100M Offers, Alex Hormozi shows you “How to charge lots of money for stuff.”
+
 Chapter 3. The Commodity Problem
-In Chapter 3 of $100M Offers, Alex Hormozi illustrates the fundamental problem with
-commoditization and how Grand Slam Offers solves that. You are either growing or dying, as
-maintenance is a myth. Therefore, you need to be growing with three simple things:
+
+In Chapter 3 of $100M Offers, Alex Hormozi illustrates the fundamental problem with commoditization and how Grand Slam Offers solves that. You are either growing or dying, as maintenance is a myth. Therefore, you need to be growing with three simple things:
 1. Get More Customers
-2. 3. Increase their Average Purchase Value
-Get Them to Buy More Times
+2. Increase their average purchase value
+3. Get Them to Buy More Times
+
 The book introduces the following key business terms:
-• Gross Profit – “the revenue minus the direct cost of servicing an ADDITIONAL customer”
-• Lifetime Value – “the gross profit accrued over the entire lifetime of a customer”
-Many businesses provide readily available commodities and compete on price, which is a race
-to the bottom. However, you should sell your products based on value with a grand slam offer:
-Grand Slam Offer – “an offer you present to the marketplace that cannot be compared to any
-other product or service available, combining an attractive promotion, an unmatchable value
-proposition, a premium price, and an unbeatable guarantee with a money model (payment
-terms) that allows you to get paid to get new customers . . . forever removing the cash
-constraint on business growth”
-This offer gets you out of the pricing war and into a category of one, which results in more
-customers, at higher ticket prices, for less money. In terms of marketing, you will have:
+- Gross Profit – “the revenue minus the direct cost of servicing an ADDITIONAL customer”
+- Lifetime Value – “the gross profit accrued over the entire lifetime of a customer”
+
+Many businesses provide readily available commodities and compete on price, which is a race to the bottom. However, you should sell your products based on value with a grand slam offer:
+Grand Slam Offer – “an offer you present to the marketplace that cannot be compared to any other product or service available, combining an attractive promotion, an unmatchable value proposition, a premium price, and an unbeatable guarantee with a money model (payment terms) that allows you to get paid to get new customers . . . forever removing the cash constraint on business growth”.
+This offer gets you out of the pricing war and into a category of one, which results in more customers, at higher ticket prices, for less money. In terms of marketing, you will have:
 1. Increased Response Rates
 2. Increased Conversion
 3. Premium Prices
+
 Chapter 4. Finding The Right Market -- A Starving Crowd
-In Chapter 4 of $100M Offers, Alex Hormozi focuses on finding the correct market to apply our
-pricing strategies. You should avoid choosing a bad market. Instead, you can pick a great market
-with demand by looking at four indicators:
-1. 2. 3. 4. Massive Pain: Your prospects must have a desperate need, not want, for your offer.
-Purchasing Power: Your prospects must afford or access the money needed to buy.
-Easy to Target: Your audience should be in easy-to-target markets.
-Growing: The market should be growing to make things move faster.
-$100M Offers by Alex Hormozi | 
-First, start with the three primary markets resembling the core human pains: Health, Wealth,
-and Relationships. Then, find a subgroup in one of these larger markets that is growing, has the
-buying power, and is easy to target. Ultimately, picking a great market matters much more than
-your offer strength and persuasion skill:
+
+In Chapter 4 of $100M Offers, Alex Hormozi focuses on finding the correct market to apply our pricing strategies. You should avoid choosing a bad market. Instead, you can pick a great market with demand by looking at four indicators:
+1. Massive Pain: Your prospects must have a desperate need, not want, for your offer.
+2. Purchasing Power: Your prospects must afford or access the money needed to buy.
+3. Easy to Target: Your audience should be in easy-to-target markets.
+4. Growing: The market should be growing to make things move faster.
+
+First, start with the three primary markets resembling the core human pains: Health, Wealth, and Relationships. Then, find a subgroup in one of these larger markets that is growing, has the buying power, and is easy to target. Ultimately, picking a great market matters much more than your offer strength and persuasion skill:
 Starving Crowd (market) > Offer Strength > Persuasion Skills
-Next, you need to commit to a niche until you have found a great offer. The niches will make
-you more money as you can charge more for a similar product. In the process of committing,
-you will try out many offers and failures. Therefore, you must be resilient, as you will eventually
-succeed.
-If you find a crazy niche market, take advantage of it. And if you can pair the niche with a Grand
-Slam Offer, you will probably never need to work again.
+
+Next, you need to commit to a niche until you have found a great offer. The niches will make you more money as you can charge more for a similar product. In the process of committing, you will try out many offers and failures. Therefore, you must be resilient, as you will eventually succeed.
+
+If you find a crazy niche market, take advantage of it. And if you can pair the niche with a Grand Slam Offer, you will probably never need to work again.
+
 Chapter 5. Pricing: Charge What It’s Worth
-In Chapter 5 of $100M Offers, Alex Hormozi advocates that you charge a premium as it allows
-you to do things no one else can to make your clients successful.
-Warren Buffet has said, “Price is what you pay. Value is what you get.” Thus, people buy to get
-a deal for what they are getting (value) is worth more than what they are giving in exchange for
-it (price).” When someone perceives the value dipping lower than the price, they stop buying.
-Avoid lowering prices to improve the price-value gap because you will fall into a vicious cycle,
-and your business will lose money and impact. Instead, you want to improve the gap by raising
-your price after sufficiently increasing the value to the customer. As a result, the virtuous cycle
-works for you and your business profits significantly.
-$100M Offers by Alex Hormozi | 
-Further, you must have clients fully committed by offering a service where they must pay high
-enough and take action required to achieve results or solve issues. Higher levels of investment
-correlate to a higher likelihood of accomplishing the positive outcome.
-$100M Offers by Alex Hormozi | 
+
+In Chapter 5 of $100M Offers, Alex Hormozi advocates that you charge a premium as it allows you to do things no one else can to make your clients successful.
+Warren Buffet has said, “Price is what you pay. Value is what you get.” Thus, people buy to get a deal for what they are getting (value) is worth more than what they are giving in exchange for it (price).”
+When someone perceives the value dipping lower than the price, they stop buying.
+Avoid lowering prices to improve the price-value gap because you will fall into a vicious cycle, and your business will lose money and impact. Instead, you want to improve the gap by raising your price after sufficiently increasing the value to the customer. As a result, the virtuous cycle works for you and your business profits significantly.
+
+Further, you must have clients fully committed by offering a service where they must pay high enough and take action required to achieve results or solve issues. Higher levels of investment correlate to a higher likelihood of accomplishing the positive outcome.
+
 Section III: Value - Create Your Offer
-In Section III of $100M Offers, Alex Hormozi shows you “How to make something so good
-people line up to buy.”
+
+In Section III of $100M Offers, Alex Hormozi shows you “How to make something so good people line up to buy.”
+
 Chapter 6. The Value Equation
-In Chapter 6 of $100M Offers, Alex Hormozi introduces the value equation. Most entrepreneurs
-think that charging a lot is wrong, but you should “charge as much money for your products or
-services as humanly possible.” However, never charge more than what they are worth.
-You must understand the value to charge the most for your goods and services. Further, you
-should price them much more than the cost of fulfillment. The Value Equation quantifies the
-four variables that create the value for any offer:
-Value is based on the perception of reality. Thus, your prospect must perceive the first two
-factors increasing and the second two factors decreasing to perceive value in their mind:
-1. 2. 3. 4. The Dream Outcome (Goal: Increase) –
-“the expression of the feelings and
-experiences the prospect has envisioned in their mind; the gap between their
-current reality and their dreams”
-Perceived Likelihood of Achievement (Goal: Increase) – the probability that the
-purchase will work and achieve the result that the prospect is looking for
-Perceived Time Delay Between Start and Achievement (Goal: Decrease) –
-“the time
-between a client buying and receiving the promised benefit;” this driver consists of
-long-term outcome and short-term experience
-Perceived Effort & Sacrifice (Goal: Decrease) – “the ancillary costs or other costs
-accrued” of effort and sacrifice; supports why “done for you services” are almost
-always more expensive than “do-it-yourself”
+
+In Chapter 6 of $100M Offers, Alex Hormozi introduces the value equation. Most entrepreneurs think that charging a lot is wrong, but you should “charge as much money for your products or services as humanly possible.” However, never charge more than what they are worth.
+You must understand the value to charge the most for your goods and services. Further, you should price them much more than the cost of fulfillment. The Value Equation quantifies the four variables that create the value for any offer:
+Value is based on the perception of reality. Thus, your prospect must perceive the first two factors increasing and the second two factors decreasing to perceive value in their mind:
+1. The Dream Outcome (Goal: Increase) – “the expression of the feelings and experiences the prospect has envisioned in their mind; the gap between their current reality and their dreams”
+2. Perceived Likelihood of Achievement (Goal: Increase) – the probability that the purchase will work and achieve the result that the prospect is looking for
+3. Perceived Time Delay Between Start and Achievement (Goal: Decrease) – “the time between a client buying and receiving the promised benefit;” this driver consists of long-term outcome and short-term experience
+4. Perceived Effort & Sacrifice (Goal: Decrease) – “the ancillary costs or other costs accrued” of effort and sacrifice; supports why “done for you services” are almost always more expensive than “do-it-yourself”
+
 Chapter 7. Free Goodwill
-In Chapter 7, Alex Hormozi asks you to leave a review of $100M Offers if you have gotten value
-so far to help reach more people.
-$100M Offers by Alex Hormozi | 
-“People who help others (with zero expectation) experience higher levels of fulfillment, live
-longer, and make more money.” And so, “if you introduce something valuable to someone,
-they associate that value with you.”
+
+In Chapter 7, Alex Hormozi asks you to leave a review of $100M Offers if you have gotten value so far to help reach more people.
+
+“People who help others (with zero expectation) experience higher levels of fulfillment, live longer, and make more money.” And so, “if you introduce something valuable to someone, they associate that value with you.”
+
 Chapter 8. The Thought Process
-In Chapter 8 of $100M Offers, Alex Hormozi shows you the difference between convergent and
-divergent problem solving:
-• Convergent – problem solving where there are many known variables with unchanging
-conditions to converge on a singular answer
-• Divergent – problem solving in which there are many solutions to a singular problem
-with known variables, unknown variables, and dynamic conditions
-Exercise: Set a timer for 2 minutes and “write down as many different uses of a brick as you can
-possibly think of.”
-This exercise illustrates that “every offer has building blocks, the pieces that when combined
-make an offer irresistible.” You need to use divergent thinking to determine how to combine
-the elements to provide value.
+
+In Chapter 8 of $100M Offers, Alex Hormozi shows you the difference between convergent and divergent problem solving:
+- Convergent – problem solving where there are many known variables with unchanging conditions to converge on a singular answer
+- Divergent – problem solving in which there are many solutions to a singular problem with known variables, unknown variables, and dynamic conditions
+
+Exercise: Set a timer for 2 minutes and “write down as many different uses of a brick as you can possibly think of.”
+This exercise illustrates that “every offer has building blocks, the pieces that when combined make an offer irresistible.” You need to use divergent thinking to determine how to combine the elements to provide value.
+
 Chapter 9. Creating Your Grand Slam Offer Part I: Problems & Solutions
-In Chapter 9 of $100M Offers, Alex Hormozi helps you craft the problems and solutions of your
-Grand Slam Offer:
-Step #1: Identify Dream Outcome: When thinking about the dream outcome, you need to
-determine what your customer experiences when they arrive at the destination.
-Step #2: List the Obstacles Encountered: Think of all the problems that prevent them from
-achieving their outcome or continually reaching it. Each problem has four negative elements
-that align with the four value drivers.
-Step #3: List the Obstacles as Solutions: Transform our problems into solutions by determining
-what is needed to solve each problem. Then, name each of the solutions.
+
+In Chapter 9 of $100M Offers, Alex Hormozi helps you craft the problems and solutions of your Grand Slam Offer:
+Step #1: Identify Dream Outcome: When thinking about the dream outcome, you need to determine what your customer experiences when they arrive at the destination.
+Step #2: List the Obstacles Encountered: Think of all the problems that prevent them from achieving their outcome or continually reaching it. Each problem has four negative elements that align with the four value drivers.
+Step #3: List the Obstacles as Solutions: Transform our problems into solutions by determining what is needed to solve each problem. Then, name each of the solutions.
+
 Chapter 10. Creating Your Grand Slam Offer Part II: Trim & Stack
-In Chapter 10 of $100M Offers, Alex Hormozi helps you tactically determine what you do or
-provide for your client in your Grand Slam Offer. Specifically, you need to understand trimming
-and stacking by reframing with the concept of the sales to fulfillment continuum:
-Sales to Fulfillment Continuum –
-“a continuum between ease of fulfillment and ease of sales”
-to find the sweet spot of selling something well that is easy to fulfill:
-$100M Offers by Alex Hormozi | 
+
+In Chapter 10 of $100M Offers, Alex Hormozi helps you tactically determine what you do or provide for your client in your Grand Slam Offer. Specifically, you need to understand trimming and stacking by reframing with the concept of the sales to fulfillment continuum:
+Sales to Fulfillment Continuum – “a continuum between ease of fulfillment and ease of sales” to find the sweet spot of selling something well that is easy to fulfill:
+
 The goal is “to find a sweet spot where you sell something very well that’s also easy to fulfill.”
 Alex Hormozi lives by the mantra, “Create flow. Monetize flow. Then add friction:”
-• Create Flow: Generate demand first to validate that what you have is good.
-• Monetize Flow: Get the prospect to say yes to your offer.
-• Add Friction: Create friction in the marketing or reduce the offer for the same price.
-“If this is your first Grand Slam Offer, it’s important to over-deliver like crazy,” which generates
-cash flow. Then, invest the cash flow to create systems and optimize processes to improve
-efficiency. As a result, your offer may not change, but rather the newly implemented systems
-will provide the same value to clients for significantly fewer resources.
+- Create Flow: Generate demand first to validate that what you have is good.
+- Monetize Flow: Get the prospect to say yes to your offer.
+- Add Friction: Create friction in the marketing or reduce the offer for the same price.
+
+“If this is your first Grand Slam Offer, it’s important to over-deliver like crazy,” which generates cash flow. Then, invest the cash flow to create systems and optimize processes to improve efficiency. As a result, your offer may not change, but rather the newly implemented systems will provide the same value to clients for significantly fewer resources.
+
 Finally, here are the last steps of creating the Grand Slam offer:
-Step #4: Create Your Solutions Delivery Vehicles (“The How”): Think through every possibility
-to solve each identified issue in exchange for money. There are several product delivery “cheat
-codes” for product variation or enhancement:
-1. 2. 3. 4. Attention: What level of personal attention do I want to provide?
-a. One-on-one – private and personalized
-b. Small group – intimate, small audience but not private
-c. One to many – large audience and not private
-Effort: What level of effort is expected from them?
-a. Do it Yourself (DIY) – the business helps the customer figure it out on their own
-b. Done with You (DWY) – the business coaches the customer on how to do it
-c. Done for You (DFY) – the company does it for the customer
-Support: If doing something live, what setting or medium do I want to deliver it in?
-a. In-person or support via phone, email, text, Zoom, chat, etc.
-Consumption: If doing a recording, how do I want them to consume it?
-a. Audio, Video, or Written materials.
-$100M Offers by Alex Hormozi | 
-5. 6. 7. Speed & Convenience: How quickly do we want to reply? On what days and hours?
-a. All-day (24/7), Workday (9-5), Time frame (within 5 minutes, 1 hour, or 1 day)
-10x Test: What would I provide if my customers paid me 10x my price (or $100,000)?
-1/10th Test: How can I ensure a successful outcome if they paid me 1/10th of the price?
-Step #5a: Trim Down the Possibilities: From your huge list of possibilities, determine those that
-provide the highest value to the customer while having the lowest cost to the business. Remove
-the high cost and low value items, followed by the low cost and low value items. The remaining
-items should be (1) low cost, high value, and (2) high cost, high value.
-Step #5b: Stack to Configure the Most Value: Combine the high value items together to create
-the ultimate high value deliverable. This Grand Slam Offer is unique, “differentiated, and unable
-to be compared to anything else in the marketplace.”
-$100M Offers by Alex Hormozi | 
+Step #4: Create Your Solutions Delivery Vehicles (“The How”): Think through every possibility to solve each identified issue in exchange for money. There are several product delivery “cheat codes” for product variation or enhancement:
+1. Attention: What level of personal attention do I want to provide?
+  a. One-on-one – private and personalized
+  b. Small group – intimate, small audience but not private
+  c. One to many – large audience and not private
+
+2. Effort: What level of effort is expected from them?
+  a. Do it Yourself (DIY) – the business helps the customer figure it out on their own
+  b. Done with You (DWY) – the business coaches the customer on how to do it
+  c. Done for You (DFY) – the company does it for the customer
+
+3. Support: If doing something live, what setting or medium do I want to deliver it in?
+  a. In-person or support via phone, email, text, Zoom, chat, etc.
+
+4. Consumption: If doing a recording, how do I want them to consume it?
+  a. Audio, Video, or Written materials.
+
+5. Speed & Convenience: How quickly do we want to reply? On what days and hours?
+  a. All-day (24/7), Workday (9-5), Time frame (within 5 minutes, 1 hour, or 1 day)
+  b. 10x Test: What would I provide if my customers paid me 10x my price (or $100,000)?
+  c. 1/10th Test: How can I ensure a successful outcome if they paid me 1/10th of the price?
+
+Step #5a: Trim Down the Possibilities: From your huge list of possibilities, determine those that provide the highest value to the customer while having the lowest cost to the business. Remove the high cost and low value items, followed by the low cost and low value items. The remaining items should be (1) low cost, high value, and (2) high cost, high value.
+
+Step #5b: Stack to Configure the Most Value: Combine the high value items together to create the ultimate high value deliverable. This Grand Slam Offer is unique, “differentiated, and unable to be compared to anything else in the marketplace.”
+
 Section IV: Enhancing Your Offer
-In Section IV of $100M Offers, Alex Hormozi shows you “How to make your offer so good they
-feel stupid saying no.”
+
+In Section IV of $100M Offers, Alex Hormozi shows you “How to make your offer so good they feel stupid saying no.”
+
 Chapter 11. Scarcity, Urgency, Bonuses, Guarantees, and Naming
-In Chapter 11 of $100M Offers, Alex Hormozi discusses how to enhance the offer by
-understanding human psychology. Naval Ravikant has said that “Desire is a contract you make
-with yourself to be unhappy until you get what you want,” as it follows that:
-“People want what they can’t have. People want what other people want. People want things
-only a select few have access to.”
+
+In Chapter 11 of $100M Offers, Alex Hormozi discusses how to enhance the offer by understanding human psychology. Naval Ravikant has said that “Desire is a contract you make with yourself to be unhappy until you get what you want,” as it follows that:
+“People want what they can’t have. People want what other people want. People want things only a select few have access to.”
+
 Essentially, all marketing exists to influence the supply and demand curve:
 Therefore, you can enhance your core offer by doing the following:
-• Increase demand or desire with persuasive communication
-• Decrease or delay satisfying the desires by selling fewer units
-If you provide zero supply or desire, you will not make money and repel people. But,
-conversely, if you satisfy all the demands, you will kill your golden goose and eventually not
-make money.
-The result is engaging in a “Delicate Dance of Desire” between supply and demand to “sell the
-same products for more money than you otherwise could, and in higher volumes, than you
-otherwise would (over a longer time horizon).”
-$100M Offers by Alex Hormozi | 
-Until now, the book has focused on the internal aspects of the offer. For more on marketing,
-check out the book, The 1-Page Marketing Plan (book summary) by Allan Dib. The following
-chapters discuss the outside factors that position the product in your prospect’s mind, including
-scarcity, urgency, bonuses, guarantees, and naming.
+- Increase demand or desire with persuasive communication
+- Decrease or delay satisfying the desires by selling fewer units
+
+If you provide zero supply or desire, you will not make money and repel people. But, conversely, if you satisfy all the demands, you will kill your golden goose and eventually not make money.
+The result is engaging in a “Delicate Dance of Desire” between supply and demand to “sell the same products for more money than you otherwise could, and in higher volumes, than you otherwise would (over a longer time horizon).”
+ 
+Until now, the book has focused on the internal aspects of the offer. For more on marketing, check out the book, The 1-Page Marketing Plan (book summary) by Allan Dib. The following chapters discuss the outside factors that position the product in your prospect’s mind, including scarcity, urgency, bonuses, guarantees, and naming.
+
 Chapter 12. Scarcity
-In a transaction, “the person who needs the exchange less always has the upper hand.” In
-Chapter 12 of $100M Offers, Alex Hormozi shows you how to “use scarcity to decrease supply
-to raise prices (and indirectly increase demand through perceived exclusiveness):”
-Scarcity – the “fear of missing out” or the psychological lever of limiting the “supply or quantity
-of products or services that are available for purchase”
-Scarcity works as the “fear of loss is stronger than the desire for gain.” Therefore, so you can
-influence prospects to take action and purchase your offer with the following types of scarcity:
+
+In a transaction, “the person who needs the exchange less always has the upper hand.”
+In Chapter 12 of $100M Offers, Alex Hormozi shows you how to “use scarcity to decrease supply to raise prices (and indirectly increase demand through perceived exclusiveness):”
+Scarcity – the “fear of missing out” or the psychological lever of limiting the “supply or quantity of products or services that are available for purchase”
+Scarcity works as the “fear of loss is stronger than the desire for gain.” Therefore, so you can influence prospects to take action and purchase your offer with the following types of scarcity:
 1. Limited Supply of Seats/Slots
 2. Limited Supply of Bonuses
 3. Never Available Again
-Physical Goods: Produce limited releases of flavors, colors, designs, sizes, etc. You must sell out
-consistently with each release to effectively create scarcity. Also, let everyone know that you
-sold out as social proof to get everyone to value it.
+
+Physical Goods: Produce limited releases of flavors, colors, designs, sizes, etc. You must sell out consistently with each release to effectively create scarcity. Also, let everyone know that you sold out as social proof to get everyone to value it.
+
 Services: Limit the number of clients to cap capacity or create cadence:
-1. 2. 3. Total Business Cap – “only accepting X clients at this level of service (on-going)”
-Growth Rate Cap – “only accepting X clients per time period (on-going)”
-Cohort Cap – “only accepting X clients per class or cohort”
-Honesty: The most ethical and easiest scarcity strategy is honesty. Simply let people know how
-close you are to the cap or selling out, which creates social proof.
+1. Total Business Cap – “only accepting X clients at this level of service (on-going)”
+2. Growth Rate Cap – “only accepting X clients per time period (on-going)”
+3. Cohort Cap – “only accepting X clients per class or cohort”
+4. Honesty: The most ethical and easiest scarcity strategy is honesty. Simply let people know how close you are to the cap or selling out, which creates social proof.
+
 Chapter 13. Urgency
-In Chapter 13 of $100M Offers, Alex Hormozi shows you how to “use urgency to increase
-demand by decreasing the action threshold of a prospect.” Scarcity and urgency are frequently
-used together, but “scarcity is a function of quantity, while urgency is a function of time:”
-Urgency – the psychological lever of limiting timing and establishing deadlines for the products
-or services that are available for purchase; implement the following four methods:
-1. 2. Rolling Cohorts – accepting clients in a limited buying window per time period
-Rolling Seasonal Urgency – accepting clients during a season with a deadline to buy
-$100M Offers by Alex Hormozi | 
-3. 4. Promotional or Pricing Urgency – “using your actual offer or promotion or pricing
-structure as the thing they could miss out on”
-Exploding Opportunity – “occasionally exposing the prospect to an arbitrage
-opportunity with a ticking time clock”
+
+In Chapter 13 of $100M Offers, Alex Hormozi shows you how to “use urgency to increase demand by decreasing the action threshold of a prospect.” Scarcity and urgency are frequently used together, but “scarcity is a function of quantity, while urgency is a function of time:”
+Urgency – the psychological lever of limiting timing and establishing deadlines for the products or services that are available for purchase; implement the following four methods:
+1. Rolling Cohorts – accepting clients in a limited buying window per time period
+2. Rolling Seasonal Urgency – accepting clients during a season with a deadline to buy
+3. Promotional or Pricing Urgency – “using your actual offer or promotion or pricing structure as the thing they could miss out on”
+4. Exploding Opportunity – “occasionally exposing the prospect to an arbitrage opportunity with a ticking time clock”
+
 Chapter 14. Bonuses
-In Chapter 14 of $100M Offers, Alex Hormozi shows you how to “use bonuses to increase
-demand (and increase perceived exclusivity).” The main takeaway is that “a single offer is less
-valuable than the same offer broken into its component parts and stacked as bonuses:”
-Bonus – an addition to the core offer that “increases the prospect’s price-to-value discrepancy
-by increasing the value delivering instead of cutting the price”
-The price is anchored to the core offer, and when selling 1-on-1, you should ask for the sale
-first. Then, offer the bonuses to grow the discrepancy such that it becomes irresistible and
-compels the prospect to buy. Additionally, there are a few keys when offering bonuses:
-1. 2. 3. Always offer them a bonus.
-Give each bonus a unique name with the benefit contained in the title.
-Tell them (a) how it relates to their issue; (b) what it is; (c) how you discovered it or
-created it; and (d) how it explicitly improves their lives or provides value.
-4. 5. 6. 7. 8. 9. Prove that each bonus provides value using stats, case studies, or personal anecdotes.
-Paint a vivid mental picture of their future life and the benefits of using the bonus.
-Assign a price to each bonus and justify it.
-Provide tools and checklists rather than additional training as they are more valuable.
-Each bonus should address a specific concern or obstacle in the prospect’s mind.
-Bonuses can solve a next or future problem before the prospect even encounters it.
+
+In Chapter 14 of $100M Offers, Alex Hormozi shows you how to “use bonuses to increase demand (and increase perceived exclusivity).” The main takeaway is that “a single offer is less valuable than the same offer broken into its component parts and stacked as bonuses:”
+
+Bonus – an addition to the core offer that “increases the prospect’s price-to-value discrepancy by increasing the value delivering instead of cutting the price”
+The price is anchored to the core offer, and when selling 1-on-1, you should ask for the sale first. Then, offer the bonuses to grow the discrepancy such that it becomes irresistible and compels the prospect to buy. Additionally, there are a few keys when offering bonuses:
+1. Always offer them a bonus.
+2. Give each bonus a unique name with the benefit contained in the title.
+3. Tell them (a) how it relates to their issue; (b) what it is; (c) how you discovered it or created it; and (d) how it explicitly improves their lives or provides value.
+4. Prove that each bonus provides value using stats, case studies, or personal anecdotes.
+5. Paint a vivid mental picture of their future life and the benefits of using the bonus.
+6. Assign a price to each bonus and justify it.
+7. Provide tools and checklists rather than additional training as they are more valuable.
+8. Each bonus should address a specific concern or obstacle in the prospect’s mind.
+9. Bonuses can solve a next or future problem before the prospect even encounters it.
 10. Ensure that each bonus expands the price to value discrepancy of the entire offer.
 11. Enhance bonus value by adding scarcity and urgency to the bonus themselves.
-Further, you can partner with other businesses to provide you with their high-value goods and
-services as a part of your bonuses.” In exchange, they will get exposure to your clients for free
-or provide you with additional revenue from affiliate marketing.
+
+Further, you can partner with other businesses to provide you with their high-value goods and services as a part of your bonuses.” In exchange, they will get exposure to your clients for free or provide you with additional revenue from affiliate marketing.
+
 Chapter 15. Guarantees
-The most significant objection to any sale of a good or service is the risk that it will not work for
-a prospect. In Chapter 15 of $100M Offers, Alex Hormozi shows you how to “use guarantees to
-increase demand by reversing risk:”
-Guarantee – “a formal assurance or promise, especially that certain conditions shall be fulfilled
-relating to a product, service, or transaction”
-$100M Offers by Alex Hormozi | 
-Your guarantee gets power by telling the prospect what you will do if they do not get the
-promised result in this conditional statement: If you do not get X result in Y time period, we will
-Z.” There are four types of guarantees:
-1. 2. 3. 4. Unconditional – the strongest guarantee that allows customers to pay to try the
-product or service to see if they like it and get a refund if they don’t like it
-a. “No Questions Asked” Refund – simple but risky as it holds you accountable
-b. Satisfaction-Based Refund – triggers when a prospect is unsatisfied with service
-Conditional – a guarantee with “terms and conditions;” can incorporate the key actions
-someone needs to take to get the successful outcome
-a. Outsized Refund – additional money back attached to doing the work to qualify
-b. Service – provide work that is free of charge until X result is achieved
-c. Modified Service – grant another period Y of service or access free of charge
-d. Credit-Based – provide a refund in the form of a credit toward your other offers
-e. Personal Service – work with client one-on-one for free until X result is achieved
-f. Hotel + Airfare Perks – reimburse your product with hotel and airfare if no value
-g. Wage-Payment – pay their hourly rate if they don’t get value from your session
-h. Release of Service – cancel the contract free of charge if they stop getting value
-i. Delayed Second Payment – stop 2nd payment until the first outcome is reached
-j. First Outcome – pay ancillary costs until they reach their first outcome
-Anti-Guarantee – a non-guarantee that explicitly states “all sales are final” with a
-creative reason for why
-Implied Guarantees – a performance-based offer based on trust and transparency
-a. Performance – pay $X per sale, show, or milestone
-b. Revenue-Share – pay X% of top-line revenue or X% of revenue growth
-c. Profit-Share – pay X% of profit or X% of Gross Profit
-d. Ratchets – pay X% if over Y revenue or profit
-e. Bonuses/Triggers – pay X when Y event occurs
+
+The most significant objection to any sale of a good or service is the risk that it will not work for a prospect. In Chapter 15 of $100M Offers, Alex Hormozi shows you how to “use guarantees to increase demand by reversing risk:”
+Guarantee – “a formal assurance or promise, especially that certain conditions shall be fulfilled relating to a product, service, or transaction”
+
+Your guarantee gets power by telling the prospect what you will do if they do not get the promised result in this conditional statement: If you do not get X result in Y time period, we will Z.” There are four types of guarantees:
+1. Unconditional – the strongest guarantee that allows customers to pay to try the product or service to see if they like it and get a refund if they don’t like it
+  a. “No Questions Asked” Refund – simple but risky as it holds you accountable
+  b. Satisfaction-Based Refund – triggers when a prospect is unsatisfied with service
+2. Conditional – a guarantee with “terms and conditions;” can incorporate the key actions someone needs to take to get the successful outcome
+3. Outsized Refund – additional money back attached to doing the work to qualify
+4. Service – provide work that is free of charge until X result is achieved
+5. Modified Service – grant another period Y of service or access free of charge
+6. Credit-Based – provide a refund in the form of a credit toward your other offers
+7. Personal Service – work with client one-on-one for free until X result is achieved
+8. Hotel + Airfare Perks – reimburse your product with hotel and airfare if no value
+9. Wage-Payment – pay their hourly rate if they don’t get value from your session
+10. Release of Service – cancel the contract free of charge if they stop getting value
+11. Delayed Second Payment – stop 2nd payment until the first outcome is reached
+12. First Outcome – pay ancillary costs until they reach their first outcome
+13. Anti-Guarantee – a non-guarantee that explicitly states “all sales are final” with a creative reason for why
+14. Implied Guarantees – a performance-based offer based on trust and transparency
+15. Performance – pay $X per sale, show, or milestone
+16. Revenue-Share – pay X% of top-line revenue or X% of revenue growth
+17. Profit-Share – pay X% of profit or X% of Gross Profit
+18. Ratchets – pay X% if over Y revenue or profit
+19. Bonuses/Triggers – pay X when Y event occurs
+
 Hormozi prefers “selling service-based guarantees or setting up performance partnerships.”
 Also, you can create your own one from your prospect’s biggest fears, pain, and obstacles.
-Further, stack guarantees to show your seriousness about their outcome. Lastly, despite
-guarantees being effective, people who specially buy based on them tend to be worse clients.
+Further, stack guarantees to show your seriousness about their outcome. Lastly, despite guarantees being effective, people who specially buy based on them tend to be worse clients.
+
 Chapter 16. Naming
-“Over time, offers fatigue; and in local markets, they fatigue even faster.” In Chapter 16 of
-$100M Offers, Alex Hormozi shows you how to “use names to re-stimulate demand and expand
-awareness of your offer to your target audience.”
-“We must appropriately name our offer to attract the right avatar to our business.” You can
-rename your offer to get leads repeatedly using the five parts of the MAGIC formula:
-• Make a Magnetic Reason Why: Start with a word or phrase that provides a strong
-reason for running the promotion or presentation.
-$100M Offers by Alex Hormozi | 
-• Announce Your Avatar: Broadcast specifically “who you are looking for and who you are
-not looking for as a client.”
-• Give Them a Goal: Elaborate upon the dream outcome for your prospect to achieve.
-• Indicate a Time Interval: Specify the expected period for the client to achieve their
-dream results.
-• Complete with a Container Word: Wrap up the offer as “a bundle of lots of things put
-together” with a container word.
+
+“Over time, offers fatigue; and in local markets, they fatigue even faster.”
+In Chapter 16 of $100M Offers, Alex Hormozi shows you how to “use names to re-stimulate demand and expand awareness of your offer to your target audience.”
+“We must appropriately name our offer to attract the right avatar to our business.” You can rename your offer to get leads repeatedly using the five parts of the MAGIC formula:
+- Make a Magnetic Reason Why: Start with a word or phrase that provides a strong reason for running the promotion or presentation.
+- Announce Your Avatar: Broadcast specifically “who you are looking for and who you are not looking for as a client.”
+- Give Them a Goal: Elaborate upon the dream outcome for your prospect to achieve.
+- Indicate a Time Interval: Specify the expected period for the client to achieve their dream results.
+- Complete with a Container Word: Wrap up the offer as “a bundle of lots of things put together” with a container word.
+
 Note that you only need to use three to five components in naming your product or service.
-This amount will allow you to distinguish yourself from the competition. Further, you can create
-variations when the market offers fatigues:
-1. 2. 3. 4. 5. 6. Change the creative elements or images in your adds
-Change the body copy in your ads
-Change the headline or the “wrapper” of your offer
-Change the duration of your offer
-Change the enhancer or free/discounted component of your offer
-Change the monetization structure, the series of offers, and the associated price points
-Section V:Execution
-In Section V of $100M Offers, Alex Hormozi discusses “How to make this happen in the real
-world.” Finally, after many years of ups and downs, Alex Hormozi made his first $100K in March
-of 2017. “It was the beginning of the next chapter in his life as a business person and
-entrepreneur,” so do not give up and keep moving forward.
+This amount will allow you to distinguish yourself from the competition. Further, you can create variations when the market offers fatigues:
+1. Change the creative elements or images in your adds
+2. Change the body copy in your ads
+3. Change the headline or the “wrapper” of your offer
+4. Change the duration of your offer
+5. Change the enhancer or free/discounted component of your offer
+6. Change the monetization structure, the series of offers, and the associated price points
+
+Section V: Execution
+
+In Section V of $100M Offers, Alex Hormozi discusses “How to make this happen in the real world.” 
+Finally, after many years of ups and downs, Alex Hormozi made his first $100K in March of 2017. “It was the beginning of the next chapter in his life as a business person and entrepreneur,” so do not give up and keep moving forward.
 
 END CONTENT SUMMARY
 

patterns/create_mnemonic_phrases/readme.md

@@ -0,0 +1,37 @@
+# create_mnemonic_phrases
+
+Generate short, memorable sentences that embed Diceware‑style words **unchanged and in order**. This pattern is ideal for turning a raw Diceware word list into phrases that are easier to recall while preserving the exact secret.
+
+## What is Diceware?
+
+Diceware is a passphrase scheme that maps every possible roll of **five six‑sided dice** (11111–66666) to a unique word. Because there are `6^5 = 7776` combinations, the canonical list contains the same number of entries.
+
+### Entropy of the standard 7776‑word list
+
+```text
+words = 7776
+entropy_per_word = log2(words) ≈ 12.925 bits
+```
+
+A passphrase that strings *N* independently chosen words together therefore carries `N × 12.925 bits` of entropy—≈ 77.5 bits for six words, ≈ 129 bits for ten, and so on. Four or more words already outclass most human‑made passwords.
+
+## Pattern overview
+
+The accompanying **`system.md`** file instructs Fabric to:
+
+1. Echo the supplied words back in **bold**, separated by commas.
+2. Generate **five** distinct, short sentences that include the words **in the same order and spelling**, enabling rapid rote learning or spaced‑repetition drills.
+
+The output is deliberately minimalist—no extra commentary—so you can pipe it straight into other scripts.
+
+## Quick start
+
+```bash
+# 1  Pick five random words from any Diceware‑compatible list
+shuf -n 5 diceware_wordlist.txt | \
+  # 2  Feed them to Fabric with this pattern
+  fabric --pattern create_mnemonic_phrases -s
+```
+
+You’ll see the words echoed in bold, followed by five candidate mnemonic sentences ready for memorisation.
+

patterns/create_mnemonic_phrases/system.md

@@ -0,0 +1,67 @@
+# IDENTITY AND PURPOSE
+
+As a creative language assistant, you are responsible for creating memorable mnemonic bridges in the form of sentences from given words. The order and spelling of the words must remain unchanged. Your task is to use these words as they are given, without allowing synonyms, paraphrases or grammatical variations. First, you will output the words in exact order and in bold, followed by five short sentences containing and highlighting all the words in the given order. You need to make sure that your answers follow the required format exactly and are easy to remember.
+
+Take a moment to think step-by-step about how to achieve the best results by following the steps below.
+
+# STEPS
+
+- First, type out the words, separated by commas, in exact order and each formatted in Markdown **bold** seperately.
+ 
+- Then create five short, memorable sentences. Each sentence should contain all the given words in exactly this order, directly embedded and highlighted in bold.
+
+# INPUT FORMAT
+
+The input will be a list of words that may appear in one of the following formats:
+
+- A plain list of wordsin a row, e.g.: 
+
+        spontaneous
+        branches
+        embargo
+        intrigue
+        detours
+   
+- A list where each word is preceded by a decimal number, e.g.:
+
+        12345 spontaneous
+        54321 branches
+        32145 embargo
+        45321 intrigue
+        35124 detours
+
+In all cases:
+Ignore any decimal numbers and use only the words, in the exact order and spelling, as input.
+
+
+# OUTPUT INSTRUCTIONS
+
+- The output is **only** in Markdown format.
+
+- Output **only** the given five words in the exact order and formatted in **bold**, separated by commas.
+
+- This is followed by exactly five short, memorable sentences. Each sentence must contain all five words in exactly this order, directly embedded and formatted in **bold**.
+
+- Nothing else may be output** - no explanations, thoughts, comments, introductions or additional information. Only the formatted word list and the five sentences.
+
+- The sentences should be short and memorable!
+
+- **Make sure you follow ALL of these instructions when creating your output**.
+
+
+## EXAMPLE
+
+**spontaneous**, **branches**, **embargo**, **intrigue**, **detours**
+
+1. The **spontaneous** monkey swung through **branches**, dodging an **embargo**, chasing **intrigue**, and loving the **detours**.
+2. Her **spontaneous** idea led her into **branches** of diplomacy, breaking an **embargo**, fueled by **intrigue**, with many **detours**.
+3. A **spontaneous** road trip ended in **branches** of politics, under an **embargo**, tangled in **intrigue**, through endless **detours**.
+4. The **spontaneous** plan involved climbing **branches**, avoiding an **embargo**, drawn by **intrigue**, and full of **detours**.
+5. His **spontaneous** speech spread through **branches** of power, lifting the **embargo**, stirring **intrigue**, and opening **detours**.
+
+
+# INPUT
+
+
+
+

patterns/create_prd/system.md

@@ -1,23 +1,41 @@
-# IDENTITY
+# IDENTITY and PURPOSE
 
-// Who you are
+You are a Product Requirements Document (PRD) Generator. Your role is to transform product ideas, prompts, or descriptions into a structured PRD. This involves outlining the product’s goals, features, technical requirements, user experience considerations, and other critical elements necessary for development and stakeholder alignment.
 
-You create precise and accurate PRDs from the input you receive.
+Your purpose is to ensure clarity, alignment, and precision in product planning and execution. You must break down the product concept into actionable sections, thinking holistically about business value, user needs, functional components, and technical feasibility. Your output should be comprehensive, well-organized, and formatted consistently to meet professional documentation standards.
 
-# GOAL
+Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
 
-// What we are trying to achieve
+## STEPS
 
-1. Create a great PRD.
+* Analyze the prompt to understand the product concept, functionality, and target users.
 
-# STEPS
+* Identify and document the key sections typically found in a PRD: Overview, Objectives, Target Audience, Features, User Stories, Functional Requirements, Non-functional Requirements, Success Metrics, and Timeline.
 
-- Read through all the input given and determine the best structure for a PRD.
+* Clarify ambiguities or ask for more information if critical details are missing.
 
-# OUTPUT INSTRUCTIONS
+* Organize the content into clearly labeled sections.
 
-- Create the PRD in Markdown.
+* Maintain formal, precise language suited for business and technical audiences.
 
-# INPUT
+* Ensure each requirement is specific, testable, and unambiguous.
+
+* Use bullet points and tables where appropriate to improve readability.
+
+## OUTPUT INSTRUCTIONS
+
+* The only output format should be Markdown.
+
+* All content should be structured into clearly labeled PRD sections.
+
+* Use bullet points and subheadings to break down features and requirements.
+
+* Highlight priorities or MVP features where relevant.
+
+* Include mock data or placeholders if actual data is not provided.
+
+* Ensure you follow ALL these instructions when creating your output.
+
+## INPUT
 
 INPUT:

patterns/extract_alpha/system.md

@@ -0,0 +1,16 @@
+# IDENTITY
+
+You're an expert at finding Alpha in content.
+
+# PHILOSOPHY
+
+I love the idea of Claude Shannon's information theory where basically the only real information is the stuff that's different and anything that's the same as kind of background noise.
+
+I love that idea for novelty and surprise inside of content when I think about a presentation or a talk or a podcast or an essay or anything I'm looking for the net new ideas or the new presentation of ideas for the new frameworks of how to use ideas or combine ideas so I'm looking for a way to capture that inside of content. 
+
+# INSTRUCTIONS
+
+I want you to extract the 24 highest alpha ideas and thoughts and insights and recommendations in this piece of content, and I want you to output them in unformatted marked down in 8-word bullets written in the approachable style of Paul Graham.
+
+# INPUT
+

patterns/extract_article_wisdom/dmiessler/extract_wisdom-1.0.0/system.md

@@ -1,29 +0,0 @@
-# IDENTITY and PURPOSE
-
-You are a wisdom extraction service for text content. You are interested in wisdom related to the purpose and meaning of life, the role of technology in the future of humanity, artificial intelligence, memes, learning, reading, books, continuous improvement, and similar topics.
-
-Take a step back and think step by step about how to achieve the best result possible as defined in the steps below. You have a lot of freedom to make this work well.
-
-## OUTPUT SECTIONS
-
-1. You extract a summary of the content in 50 words or less, including who is presenting and the content being discussed into a section called SUMMARY.
-
-2. You extract the top 50 ideas from the input in a section called IDEAS:. If there are less than 50 then collect all of them.
-
-3. You extract the 15-30 most insightful and interesting quotes from the input into a section called QUOTES:. Use the exact quote text from the input.
-
-4. You extract 15-30 personal habits of the speakers, or mentioned by the speakers, in the content into a section called HABITS. Examples include but aren't limited to: sleep schedule, reading habits, things the
-
-5. You extract the 15-30 most insightful and interesting valid facts about the greater world that were mentioned in the content into a section called FACTS:.
-
-6. You extract all mentions of writing, art, and other sources of inspiration mentioned by the speakers into a section called REFERENCES. This should include any and all references to something that the speaker mentioned.
-
-7. You extract the 15-30 most insightful and interesting overall (not content recommendations from EXPLORE) recommendations that can be collected from the content into a section called RECOMMENDATIONS.
-
-## OUTPUT INSTRUCTIONS
-
-1. You only output Markdown.
-2. Do not give warnings or notes; only output the requested sections.
-3. You use numbered lists, not bullets.
-4. Do not repeat ideas, quotes, habits, facts, or references.
-5. Do not start items with the same opening words.

patterns/extract_article_wisdom/dmiessler/extract_wisdom-1.0.0/user.md

@@ -1 +0,0 @@
-CONTENT:

patterns/extract_insights/system.md

@@ -1,25 +1,21 @@
 # IDENTITY and PURPOSE
 
-You extract surprising, powerful, and interesting insights from text content. You are interested in insights related to the purpose and meaning of life, human flourishing, the role of technology in the future of humanity, artificial intelligence and its affect on humans, memes, learning, reading, books, continuous improvement, and similar topics.
+You are an expert at extracting the most surprising, powerful, and interesting insights from content. You are interested in insights related to the purpose and meaning of life, human flourishing, the role of technology in the future of humanity, artificial intelligence and its affect on humans, memes, learning, reading, books, continuous improvement, and similar topics.
 
-You create 15 word bullet points that capture the most important insights from the input.
+You create 8 word bullet points that capture the most surprising and novel insights from the input.
 
 Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
 
 # STEPS
 
-- Extract 20 to 50 of the most surprising, insightful, and/or interesting ideas from the input in a section called IDEAS, and write them on a virtual whiteboard in your mind using 15 word bullets. If there are less than 50 then collect all of them. Make sure you extract at least 20.
-
-- From those IDEAS, extract the most powerful and insightful of them and write them in a section called INSIGHTS. Make sure you extract at least 10 and up to 25.
+- Extract 10 of the most surprising and novel insights from the input.
+- Output them as 8 word bullets in order of surprise, novelty, and importance.
+- Write them in the simple, approachable style of Paul Graham.
 
 # OUTPUT INSTRUCTIONS
 
-- INSIGHTS are essentially higher-level IDEAS that are more abstracted and wise.
-
 - Output the INSIGHTS section only.
 
-- Each bullet should be 16 words in length.
-
 - Do not give warnings or notes; only output the requested sections.
 
 - You use bulleted lists for output, not numbered lists.
@@ -28,7 +24,6 @@ Take a step back and think step-by-step about how to achieve the best possible r
 
 - Ensure you follow ALL these instructions when creating your output.
 
-
 # INPUT
 
-INPUT:
+{{input}}

patterns/extract_mcp_servers/system.md

@@ -0,0 +1,64 @@
+# IDENTITY and PURPOSE
+
+You are an expert at analyzing content related to MCP (Model Context Protocol) servers. You excel at identifying and extracting mentions of MCP servers, their features, capabilities, integrations, and usage patterns.
+
+Take a step back and think step-by-step about how to achieve the best results for extracting MCP server information.
+
+# STEPS
+
+- Read and analyze the entire content carefully
+- Identify all mentions of MCP servers, including:
+  - Specific MCP server names
+  - Server capabilities and features
+  - Integration details
+  - Configuration examples
+  - Use cases and applications
+  - Installation or setup instructions
+  - API endpoints or methods exposed
+  - Any limitations or requirements
+
+# OUTPUT SECTIONS
+
+- Output a summary of all MCP servers mentioned with the following sections:
+
+## SERVERS FOUND
+
+- List each MCP server found with a 15-word description
+- Include the server name and its primary purpose
+- Use bullet points for each server
+
+## SERVER DETAILS
+
+For each server found, provide:
+- **Server Name**: The official name
+- **Purpose**: Main functionality in 25 words or less
+- **Key Features**: Up to 5 main features as bullet points
+- **Integration**: How it integrates with systems (if mentioned)
+- **Configuration**: Any configuration details mentioned
+- **Requirements**: Dependencies or requirements (if specified)
+
+## USAGE EXAMPLES
+
+- Extract any code snippets or usage examples
+- Include configuration files or setup instructions
+- Present each example with context
+
+## INSIGHTS
+
+- Provide 3-5 insights about the MCP servers mentioned
+- Focus on patterns, trends, or notable characteristics
+- Each insight should be a 20-word bullet point
+
+# OUTPUT INSTRUCTIONS
+
+- Output in clean, readable Markdown
+- Use proper heading hierarchy
+- Include code blocks with appropriate language tags
+- Do not include warnings or notes about the content
+- If no MCP servers are found, simply state "No MCP servers mentioned in the content"
+- Ensure all server names are accurately captured
+- Preserve technical details and specifications
+
+# INPUT:
+
+INPUT:

patterns/extract_product_features/dmiessler/extract_wisdom-1.0.0/system.md

@@ -1,29 +0,0 @@
-# IDENTITY and PURPOSE
-
-You are a wisdom extraction service for text content. You are interested in wisdom related to the purpose and meaning of life, the role of technology in the future of humanity, artificial intelligence, memes, learning, reading, books, continuous improvement, and similar topics.
-
-Take a step back and think step by step about how to achieve the best result possible as defined in the steps below. You have a lot of freedom to make this work well.
-
-## OUTPUT SECTIONS
-
-1. You extract a summary of the content in 50 words or less, including who is presenting and the content being discussed into a section called SUMMARY.
-
-2. You extract the top 50 ideas from the input in a section called IDEAS:. If there are less than 50 then collect all of them.
-
-3. You extract the 15-30 most insightful and interesting quotes from the input into a section called QUOTES:. Use the exact quote text from the input.
-
-4. You extract 15-30 personal habits of the speakers, or mentioned by the speakers, in the content into a section called HABITS. Examples include but aren't limited to: sleep schedule, reading habits, things the speakers always do, things they always avoid, productivity tips, diet, exercise, etc.
-
-5. You extract the 15-30 most insightful and interesting valid facts about the greater world that were mentioned in the content into a section called FACTS:.
-
-6. You extract all mentions of writing, art, and other sources of inspiration mentioned by the speakers into a section called REFERENCES. This should include any and all references to something that the speaker mentioned.
-
-7. You extract the 15-30 most insightful and interesting overall (not content recommendations from EXPLORE) recommendations that can be collected from the content into a section called RECOMMENDATIONS.
-
-## OUTPUT INSTRUCTIONS
-
-1. You only output Markdown.
-2. Do not give warnings or notes; only output the requested sections.
-3. You use numbered lists, not bullets.
-4. Do not repeat ideas, quotes, habits, facts, or references.
-5. Do not start items with the same opening words.

patterns/extract_product_features/dmiessler/extract_wisdom-1.0.0/user.md

@@ -1 +0,0 @@
-CONTENT:

patterns/extract_wisdom/dmiessler/extract_wisdom-1.0.0/system.md

@@ -1,29 +0,0 @@
-# IDENTITY and PURPOSE
-
-You are a wisdom extraction service for text content. You are interested in wisdom related to the purpose and meaning of life, the role of technology in the future of humanity, artificial intelligence, memes, learning, reading, books, continuous improvement, and similar topics.
-
-Take a step back and think step by step about how to achieve the best result possible as defined in the steps below. You have a lot of freedom to make this work well.
-
-## OUTPUT SECTIONS
-
-1. You extract a summary of the content in 50 words or less, including who is presenting and the content being discussed into a section called SUMMARY.
-
-2. You extract the top 50 ideas from the input in a section called IDEAS:. If there are less than 50 then collect all of them.
-
-3. You extract the 15-30 most insightful and interesting quotes from the input into a section called QUOTES:. Use the exact quote text from the input.
-
-4. You extract 15-30 personal habits of the speakers, or mentioned by the speakers, in the content into a section called HABITS. Examples include but aren't limited to: sleep schedule, reading habits, things the speakers always do, things they always avoid, productivity tips, diet, exercise, etc.
-
-5. You extract the 15-30 most insightful and interesting valid facts about the greater world that were mentioned in the content into a section called FACTS:.
-
-6. You extract all mentions of writing, art, and other sources of inspiration mentioned by the speakers into a section called REFERENCES. This should include any and all references to something that the speaker mentioned.
-
-7. You extract the 15-30 most insightful and interesting overall (not content recommendations from EXPLORE) recommendations that can be collected from the content into a section called RECOMMENDATIONS.
-
-## OUTPUT INSTRUCTIONS
-
-1. You only output Markdown.
-2. Do not give warnings or notes; only output the requested sections.
-3. You use numbered lists, not bullets.
-4. Do not repeat ideas, quotes, habits, facts, or references.
-5. Do not start items with the same opening words.

patterns/extract_wisdom/dmiessler/extract_wisdom-1.0.0/user.md

@@ -1 +0,0 @@
-CONTENT:

patterns/pattern_explanations.md

@@ -1,210 +1,223 @@
-Brief one-line summary from AI analysis of what each pattern does.
+# Brief one-line summary from AI analysis of what each pattern does
 
 - Key pattern to use: **suggest_pattern**, suggests appropriate fabric patterns or commands based on user input.**
 
 1. **agility_story**: Generate a user story and acceptance criteria in JSON format based on the given topic.
 2. **ai**: Interpret questions deeply and provide concise, insightful answers in Markdown bullet points.
-3. **analyse_answers**: Evaluate quiz answers for correctness based on learning objectives and generated quiz questions.
-4. **analyse_candidates**: Compare and contrast two political candidates based on key issues and policies.
-5. **analyse_cfp_submission**: Review and evaluate conference speaking session submissions based on clarity, relevance, depth, and engagement potential.
-6. **analyse_claims**: Analyse and rate truth claims with evidence, counter-arguments, fallacies, and final recommendations.
-7. **analyse_comments**: Evaluate internet comments for content, categorize sentiment, and identify reasons for praise, criticism, and neutrality.
-8. **analyse_debate**: Rate debates on insight, emotionality, and present an unbiased, thorough analysis of arguments, agreements, and disagreements.
-9. **analyse_email_headers**: Provide cybersecurity analysis and actionable insights on SPF, DKIM, DMARC, and ARC email header results.
-10. **analyse_incident**: Efficiently extract and organize key details from cybersecurity breach articles, focusing on attack type, vulnerable components, attacker and target info, incident details, and remediation steps.
-11. **analyse_interviewer_techniques**: This exercise involves analyzing interviewer techniques, identifying their unique qualities, and succinctly articulating what makes them stand out in a clear, simple format.
-12. **analyse_logs**: Analyse server log files to identify patterns, anomalies, and issues, providing data-driven insights and recommendations for improving server reliability and performance.
-13. **analyse_malware**: Analyse malware details, extract key indicators, techniques, and potential detection strategies, and summarize findings concisely for a malware analyst's use in identifying and responding to threats.
-14. **analyse_military_strategy**: Analyse a historical battle, offering in-depth insights into strategic decisions, strengths, weaknesses, tactical approaches, logistical factors, pivotal moments, and consequences for a comprehensive military evaluation.
-15. **analyse_mistakes**: Analyse past mistakes in thinking patterns, map them to current beliefs, and offer recommendations to improve accuracy in predictions.
-16. **analyse_paper**: Analyses research papers by summarizing findings, evaluating rigor, and assessing quality to provide insights for documentation and review.
-17. **analyse_patent**: Analyse a patent's field, problem, solution, novelty, inventive step, and advantages in detail while summarizing and extracting keywords.
-18. **analyze_personality**: Performs a deep psychological analysis of a person in the input, focusing on their behavior, language, and psychological traits.
-19. **analyze_presentation**: Reviews and critiques presentations by analyzing the content, speaker's underlying goals, self-focus, and entertainment value.
-20. **analyze_product_feedback**: A prompt for analyzing and organizing user feedback by identifying themes, consolidating similar comments, and prioritizing them based on usefulness.
-21. **analyze_proposition**: Analyzes a ballot proposition by identifying its purpose, impact, arguments for and against, and relevant background information.
-22. **analyze_prose**: Evaluates writing for novelty, clarity, and prose, providing ratings, improvement recommendations, and an overall score.
-23. **analyze_prose_json**: Evaluates writing for novelty, clarity, prose, and provides ratings, explanations, improvement suggestions, and an overall score in a JSON format.
-24. **analyze_prose_pinker**: Evaluates prose based on Steven Pinker's The Sense of Style, analyzing writing style, clarity, and bad writing elements.
-25. **analyze_risk**: Conducts a risk assessment of a third-party vendor, assigning a risk score and suggesting security controls based on analysis of provided documents and vendor website.
-26. **analyze_sales_call**: Rates sales call performance across multiple dimensions, providing scores and actionable feedback based on transcript analysis.
-27. **analyze_spiritual_text**: Compares and contrasts spiritual texts by analyzing claims and differences with the King James Bible.
-28. **analyze_tech_impact**: Analyzes the societal impact, ethical considerations, and sustainability of technology projects, evaluating their outcomes and benefits.
-29. **analyze_threat_report**: Extracts surprising insights, trends, statistics, quotes, references, and recommendations from cybersecurity threat reports, summarizing key findings and providing actionable information.
-30. **analyse_threat_report_cmds**: Extract and synthesize actionable cybersecurity commands from provided materials, incorporating command-line arguments and expert insights for pentesters and non-experts.
-31. **analyse_threat_report_trends**: Extract up to 50 surprising, insightful, and interesting trends from a cybersecurity threat report in markdown format.
-32. **answer_interview_question**: Generates concise, tailored responses to technical interview questions, incorporating alternative approaches and evidence to demonstrate the candidate's expertise and experience.
-33. **ask_secure_by_design_questions**: Generates a set of security-focused questions to ensure a project is built securely by design, covering key components and considerations.
-34. **ask_uncle_duke**: Coordinates a team of AI agents to research and produce multiple software development solutions based on provided specifications, and conducts detailed code reviews to ensure adherence to best practices.
-35. **capture_thinkers_work**: Analyze philosophers or philosophies and provide detailed summaries about their teachings, background, works, advice, and related concepts in a structured template.
-36. **check_agreement**: Analyze contracts and agreements to identify important stipulations, issues, and potential gotchas, then summarize them in Markdown.
-37. **clean_text**: Fix broken or malformatted text by correcting line breaks, punctuation, capitalization, and paragraphs without altering content or spelling.
-38. **coding_master**: Explain a coding concept to a beginner, providing examples, and formatting code in markdown with specific output sections like ideas, recommendations, facts, and insights.
-39. **compare_and_contrast**: Compare and contrast a list of items in a markdown table, with items on the left and topics on top.
-40. **convert_to_markdown**: Convert content to clean, complete Markdown format, preserving all original structure, formatting, links, and code blocks without alterations.
-41. **create_5_sentence_summary**: Create concise summaries or answers to input at 5 different levels of depth, from 5 words to 1 word.
-42. **create_academic_paper**: Generate a high-quality academic paper in LaTeX format with clear concepts, structured content, and a professional layout.
-43. **create_ai_jobs_analysis**: Analyze job categories' susceptibility to automation, identify resilient roles, and provide strategies for personal adaptation to AI-driven changes in the workforce.
-44. **create_aphorisms**: Find and generate a list of brief, witty statements.
-45. **create_art_prompt**: Generates a detailed, compelling visual description of a concept, including stylistic references and direct AI instructions for creating art.
-46. **create_better_frame**: Identifies and analyzes different frames of interpreting reality, emphasizing the power of positive, productive lenses in shaping outcomes.
-47. **create_coding_project**: Generate wireframes and starter code for any coding ideas that you have.
-48. **create_command**: Helps determine the correct parameters and switches for penetration testing tools based on a brief description of the objective.
-49. create_cyber_summary: Summarizes cybersecurity threats, vulnerabilities, incidents, and malware with a 25-word summary and categorized bullet points, after thoroughly analyzing and mapping the provided input.
-50. **create_design_document**: Creates a detailed design document for a system using the C4 model, addressing business and security postures, and including a system context diagram.
-51. **create_diy**: Creates structured "Do It Yourself" tutorial patterns by analyzing prompts, organizing requirements, and providing step-by-step instructions in Markdown format.
-52. **create_formal_email**: Crafts professional, clear, and respectful emails by analyzing context, tone, and purpose, ensuring proper structure and formatting.
-53. **create_git_diff_commit**: Generates Git commands and commit messages for reflecting changes in a repository, using conventional commits and providing concise shell commands for updates.
-54. **create_graph_from_input**: Generates a CSV file with progress-over-time data for a security program, focusing on relevant metrics and KPIs.
-55. **create_hormozi_offer**: Creates a customized business offer based on principles from Alex Hormozi's book, "$100M Offers."
-56. **create_idea_compass**: Organizes and structures ideas by exploring their definition, evidence, sources, and related themes or consequences.
-57. **create_investigation_visualization**: Creates detailed Graphviz visualizations of complex input, highlighting key aspects and providing clear, well-annotated diagrams for investigative analysis and conclusions.
-58. **create_keynote**: Creates TED-style keynote presentations with a clear narrative, structured slides, and speaker notes, emphasizing impactful takeaways and cohesive flow.
-59. **create_logo**: Creates simple, minimalist company logos without text, generating AI prompts for vector graphic logos based on input.
-60. **create_markmap_visualization**: Transforms complex ideas into clear visualizations using MarkMap syntax, simplifying concepts into diagrams with relationships, boxes, arrows, and labels.
-61. **create_mermaid_visualization**: Creates detailed, standalone visualizations of concepts using Mermaid (Markdown) syntax, ensuring clarity and coherence in diagrams.
-62. **create_mermaid_visualization_for_github**: Creates standalone, detailed visualizations using Mermaid (Markdown) syntax to effectively explain complex concepts, ensuring clarity and precision.
-63. **create_micro_summary**: Summarizes content into a concise, 20-word summary with main points and takeaways, formatted in Markdown.
-64. **create_network_threat_landscape**: Analyzes open ports and services from a network scan and generates a comprehensive, insightful, and detailed security threat report in Markdown.
-65. **create_newsletter_entry**: Condenses provided article text into a concise, objective, newsletter-style summary with a title in the style of Frontend Weekly.
-66. **create_npc**: Generates a detailed D&D 5E NPC, including background, flaws, stats, appearance, personality, goals, and more in Markdown format.
-67. **create_pattern**: Extracts, organizes, and formats LLM/AI prompts into structured sections, detailing the AI’s role, instructions, output format, and any provided examples for clarity and accuracy.
-68. **create_prd**: Creates a precise Product Requirements Document (PRD) in Markdown based on input.
-69. **create_prediction_block**: Extracts and formats predictions from input into a structured Markdown block for a blog post.
-70. **create_quiz**: Creates a three-phase reading plan based on an author or topic to help the user become significantly knowledgeable, including core, extended, and supplementary readings.
-71. **create_reading_plan**: Generates review questions based on learning objectives from the input, adapted to the specified student level, and outputs them in a clear markdown format.
-72. **create_recursive_outline**: Breaks down complex tasks or projects into manageable, hierarchical components with recursive outlining for clarity and simplicity.
-73. **create_report_finding**: Creates a detailed, structured security finding report in markdown, including sections on Description, Risk, Recommendations, References, One-Sentence-Summary, and Quotes.
-74. **create_rpg_summary**: Summarizes an in-person RPG session with key events, combat details, player stats, and role-playing highlights in a structured format.
-75. **create_security_update**: Creates concise security updates for newsletters, covering stories, threats, advisories, vulnerabilities, and a summary of key issues.
-76. **create_show_intro**: Creates compelling short intros for podcasts, summarizing key topics and themes discussed in the episode.
-77. **create_sigma_rules**: Extracts Tactics, Techniques, and Procedures (TTPs) from security news and converts them into Sigma detection rules for host-based detections.
-78. **create_story_explanation**: Summarizes complex content in a clear, approachable story format that makes the concepts easy to understand.
-79. **create_stride_threat_model**: Create a STRIDE-based threat model for a system design, identifying assets, trust boundaries, data flows, and prioritizing threats with mitigations.
-80. **create_summary**: Summarizes content into a 20-word sentence, 10 main points (16 words max), and 5 key takeaways in Markdown format.
-81. **create_tags**: Identifies at least 5 tags from text content for mind mapping tools, including authors and existing tags if present.
-82. **create_threat_scenarios**: Identifies likely attack methods for any system by providing a narrative-based threat model, balancing risk and opportunity.
-83. **create_ttrc_graph**: Creates a CSV file showing the progress of Time to Remediate Critical Vulnerabilities over time using given data.
-84. **create_ttrc_narrative**: Creates a persuasive narrative highlighting progress in reducing the Time to Remediate Critical Vulnerabilities metric over time.
-85. **create_upgrade_pack**: Extracts world model and task algorithm updates from content, providing beliefs about how the world works and task performance.
-86. **create_user_story**: Writes concise and clear technical user stories for new features in complex software programs, formatted for all stakeholders.
-87. **create_video_chapters**: Extracts interesting topics and timestamps from a transcript, providing concise summaries of key moments.
-88. **create_visualization**: Transforms complex ideas into visualizations using intricate ASCII art, simplifying concepts where necessary.
-89. **dialog_with_socrates**: Engages in deep, meaningful dialogues to explore and challenge beliefs using the Socratic method.
-90. **enrich_blog_post**: Enhances Markdown blog files by applying instructions to improve structure, visuals, and readability for HTML rendering.
-91. **explain_code**: Explains code, security tool output, configuration text, and answers questions based on the provided input.
-92. **explain_docs**: Improves and restructures tool documentation into clear, concise instructions, including overviews, usage, use cases, and key features.
-93. **explain_math**: Helps you understand mathematical concepts in a clear and engaging way.
-94. **explain_project**: Summarizes project documentation into clear, concise sections covering the project, problem, solution, installation, usage, and examples.
-95. **explain_terms**: Produces a glossary of advanced terms from content, providing a definition, analogy, and explanation of why each term matters.
-96. **export_data_as_csv**: Extracts and outputs all data structures from the input in properly formatted CSV data.
-97. **extract_algorithm_update_recommendations**: Extracts concise, practical algorithm update recommendations from the input and outputs them in a bulleted list.
-98. **extract_article_wisdom**: Extracts surprising, insightful, and interesting information from content, categorizing it into sections like summary, ideas, quotes, facts, references, and recommendations.
-99. **extract_book_ideas**: Extracts and outputs 50 to 100 of the most surprising, insightful, and interesting ideas from a book's content.
-100. **extract_book_recommendations**: Extracts and outputs 50 to 100 practical, actionable recommendations from a book's content.
-101. **extract_business_ideas**: Extracts top business ideas from content and elaborates on the best 10 with unique differentiators.
-102. **extract_controversial_ideas**: Extracts and outputs controversial statements and supporting quotes from the input in a structured Markdown list.
-103. **extract_core_message**: Extracts and outputs a clear, concise sentence that articulates the core message of a given text or body of work.
-104. **extract_ctf_writeup**: Extracts a short writeup from a warstory-like text about a cyber security engagement.
-105. **extract_extraordinary_claims**: Extracts and outputs a list of extraordinary claims from conversations, focusing on scientifically disputed or false statements.
-106. **extract_ideas**: Extracts and outputs all the key ideas from input, presented as 15-word bullet points in Markdown.
-107. **extract_insights**: Extracts and outputs the most powerful and insightful ideas from text, formatted as 16-word bullet points in the INSIGHTS section, also IDEAS section.
-108. **extract_insights_dm**: Extracts and outputs all valuable insights and a concise summary of the content, including key points and topics discussed.
-109. **extract_instructions**: Extracts clear, actionable step-by-step instructions and main objectives from instructional video transcripts, organizing them into a concise list.
-110. **extract_jokes**: Extracts jokes from text content, presenting each joke with its punchline in separate bullet points.
-111. **extract_latest_video**: Extracts the latest video URL from a YouTube RSS feed and outputs the URL only.
-112. **extract_main_idea**: Extracts the main idea and key recommendation from the input, summarizing them in 15-word sentences.
-113. **extract_most_redeeming_thing**: Extracts the most redeeming aspect from an input, summarizing it in a single 15-word sentence.
-114. **extract_patterns**: Extracts and analyzes recurring, surprising, and insightful patterns from input, providing detailed analysis and advice for builders.
-115. **extract_poc**: Extracts proof of concept URLs and validation methods from security reports, providing the URL and command to run.
-116. **extract_predictions**: Extracts predictions from input, including specific details such as date, confidence level, and verification method.
-117. **extract_primary_problem**: Extracts the primary problem with the world as presented in a given text or body of work.
-118. **extract_primary_solution**: Extracts the primary solution for the world as presented in a given text or body of work.
-119. **extract_product_features**: Extracts and outputs a list of product features from the provided input in a bulleted format.
-120. **extract_questions**: Extracts and outputs all questions asked by the interviewer in a conversation or interview.
-121. **extract_recipe**: Extracts and outputs a recipe with a short meal description, ingredients with measurements, and preparation steps.
-122. **extract_recommendations**: Extracts and outputs concise, practical recommendations from a given piece of content in a bulleted list.
-123. **extract_references**: Extracts and outputs a bulleted list of references to art, stories, books, literature, and other sources from content.
-124. **extract_skills**: Extracts and classifies skills from a job description into a table, separating each skill and classifying it as either hard or soft.
-125. **extract_song_meaning**: Analyzes a song to provide a summary of its meaning, supported by detailed evidence from lyrics, artist commentary, and fan analysis.
-126. **extract_sponsors** Extracts and lists official sponsors and potential sponsors from a provided transcript.
-127. **extract_videoid**: Extracts and outputs the video ID from any given URL.
-128. **extract_wisdom**: Extracts surprising, insightful, and interesting information from text on topics like human flourishing, AI, learning, and more.
-129. **extract_wisdom_agents**: Extracts valuable insights, ideas, quotes, and references from content, emphasizing topics like human flourishing, AI, learning, and technology.
-130. **extract_wisdom_dm**: Extracts all valuable, insightful, and thought-provoking information from content, focusing on topics like human flourishing, AI, learning, and technology.
-131. **extract_wisdom_nometa**: Extracts insights, ideas, quotes, habits, facts, references, and recommendations from content, focusing on human flourishing, AI, technology, and related topics.
-132. **find_hidden_message**: Extracts overt and hidden political messages, justifications, audience actions, and a cynical analysis from content.
-133. **find_logical_fallacies**: Identifies and analyzes fallacies in arguments, classifying them as formal or informal with detailed reasoning.
-134. **get_wow_per_minute**: Determines the wow-factor of content per minute based on surprise, novelty, insight, value, and wisdom, measuring how rewarding the content is for the viewer.
-135. **get_youtube_rss**: Returns the RSS URL for a given YouTube channel based on the channel ID or URL.
-136. **humanize**: Rewrites AI-generated text to sound natural, conversational, and easy to understand, maintaining clarity and simplicity.
-137. **identify_dsrp_distinctions**: Encourages creative, systems-based thinking by exploring distinctions, boundaries, and their implications, drawing on insights from prominent systems thinkers.
-138. **identify_dsrp_perspectives**: Explores the concept of distinctions in systems thinking, focusing on how boundaries define ideas, influence understanding, and reveal or obscure insights.
-139. **identify_dsrp_relationships**: Encourages exploration of connections, distinctions, and boundaries between ideas, inspired by systems thinkers to reveal new insights and patterns in complex systems.
-140. **identify_dsrp_systems**: Encourages organizing ideas into systems of parts and wholes, inspired by systems thinkers to explore relationships and how changes in organization impact meaning and understanding.
-141. **identify_job_stories**: Identifies key job stories or requirements for roles.
-142. **improve_academic_writing**: Refines text into clear, concise academic language while improving grammar, coherence, and clarity, with a list of changes.
-143. **improve_prompt**: Improves an LLM/AI prompt by applying expert prompt writing strategies for better results and clarity.
-144. **improve_report_finding**: Improves a penetration test security finding by providing detailed descriptions, risks, recommendations, references, quotes, and a concise summary in markdown format.
-145. **improve_writing**: Refines text by correcting grammar, enhancing style, improving clarity, and maintaining the original meaning. skills.
-146. **judge_output**: Evaluates Honeycomb queries by judging their effectiveness, providing critiques and outcomes based on language nuances and analytics relevance.
-147. **label_and_rate**: Labels content with up to 20 single-word tags and rates it based on idea count and relevance to human meaning, AI, and other related themes, assigning a tier (S, A, B, C, D) and a quality score.
-148. **md_callout**: Classifies content and generates a markdown callout based on the provided text, selecting the most appropriate type.
-149. **official_pattern_template**: Template to use if you want to create new fabric patterns.
-150. **prepare_7s_strategy**: Prepares a comprehensive briefing document from 7S's strategy capturing organizational profile, strategic elements, and market dynamics with clear, concise, and organized content.
-151. **provide_guidance**: Provides psychological and life coaching advice, including analysis, recommendations, and potential diagnoses, with a compassionate and honest tone.
-152. **rate_ai_response**: Rates the quality of AI responses by comparing them to top human expert performance, assigning a letter grade, reasoning, and providing a 1-100 score based on the evaluation.
-153. **rate_ai_result**: Assesses the quality of AI/ML/LLM work by deeply analyzing content, instructions, and output, then rates performance based on multiple dimensions, including coverage, creativity, and interdisciplinary thinking.
-154. **rate_content**: Labels content with up to 20 single-word tags and rates it based on idea count and relevance to human meaning, AI, and other related themes, assigning a tier (S, A, B, C, D) and a quality score.
-155. **rate_value**: Produces the best possible output by deeply analyzing and understanding the input and its intended purpose.
-156. **raw_query**: Fully digests and contemplates the input to produce the best possible result based on understanding the sender's intent.
-157. **raycast**: Some scripts for Raycast, but think u need pro Raycast AI to use it
-158. **recommend_artists**: Recommends a personalized festival schedule with artists aligned to your favorite styles and interests, including rationale.
-159. **recommend_pipeline_upgrades**: Optimizes vulnerability-checking pipelines by incorporating new information and improving their efficiency, with detailed explanations of changes.
-160. **recommend_talkpanel_topics**: Produces a clean set of proposed talks or panel talking points for a person based on their interests and goals, formatted for submission to a conference organizer.
-161. **refine_design_document**: Refines a design document based on a design review by analyzing, mapping concepts, and implementing changes using valid Markdown.
-162. **review_design**: Reviews and analyzes architecture design, focusing on clarity, component design, system integrations, security, performance, scalability, and data management.
-163. **sanitize_broken_html_to_markdown**: Converts messy HTML into clean, properly formatted Markdown, applying custom styling and ensuring compatibility with Vite.
-164. **show_fabric_options_markmap**: Visualizes the functionality of the Fabric framework by representing its components, commands, and features based on the provided input.
-165. **solve_with_cot**: Provides detailed, step-by-step responses with chain of thought reasoning, using structured thinking, reflection, and output sections.
-166. **suggest_pattern**: Suggests appropriate fabric patterns or commands based on user input, providing clear explanations and options for users.
-167. **summarize**: Summarizes content into a 20-word sentence, main points, and takeaways, formatted with numbered lists in Markdown.
-168. **summarize_debate**: Summarizes debates, identifies primary disagreement, extracts arguments, and provides analysis of evidence and argument strength to predict outcomes.
-169. **summarize_git_changes**: Summarizes recent project updates from the last 7 days, focusing on key changes with enthusiasm.
-170. **summarize_git_diff**: Summarizes and organizes Git diff changes with clear, succinct commit messages and bullet points.
-171. **summarize_lecture**: Extracts relevant topics, definitions, and tools from lecture transcripts, providing structured summaries with timestamps and key takeaways.
-172. **summarize_legislation**: Summarizes complex political proposals and legislation by analyzing key points, proposed changes, and providing balanced, positive, and cynical characterizations.
-173. **summarize_meeting**: Analyzes meeting transcripts to extract a structured summary, including an overview, key points, tasks, decisions, challenges, timeline, references, and next steps.
-174. **summarize_micro**: Summarizes content into a 20-word sentence, 3 main points, and 3 takeaways, formatted in clear, concise Markdown.
-175. **summarize_newsletter**: Extracts the most meaningful, interesting, and useful content from a newsletter, summarizing key sections such as content, opinions, tools, companies, and follow-up items in clear, structured Markdown.
-176. **summarize_paper**: Summarizes an academic paper by detailing its title, authors, technical approach, distinctive features, experimental setup, results, advantages, limitations, and conclusion in a clear, structured format using human-readable Markdown.
-177. **summarize_prompt**: Summarizes AI chat prompts by describing the primary function, unique approach, and expected output in a concise paragraph. The summary is focused on the prompt's purpose without unnecessary details or formatting.
-178. **summarize_pull-requests**: Summarizes pull requests for a coding project by providing a summary and listing the top PRs with human-readable descriptions.
-179. **summarize_rpg_session**: Summarizes a role-playing game session by extracting key events, combat stats, character changes, quotes, and more.
-180. **t_analyse_challenge_handling**: Provides 8-16 word bullet points evaluating how well challenges are being addressed, calling out any lack of effort.
-181. **t_check_metrics**: Analyzes deep context from the TELOS file and input instruction, then provides a wisdom-based output while considering metrics and KPIs to assess recent improvements.
-182. **t_create_h3_career**: Summarizes context and produces wisdom-based output by deeply analyzing both the TELOS File and the input instruction, considering the relationship between the two.
-183. **t_create_opening_sentences**: Describes from TELOS file the person’s identity, goals, and actions in 4 concise, 32-word bullet points, humbly.
-184. **t_describe_life_outlook**: Describes from TELOS file a person's life outlook in 5 concise, 16-word bullet points.
-185. **t_extract_intro_sentences**: Summarizes from TELOS file a person's identity, work, and current projects in 5 concise and grounded bullet points.
-186. **t_extract_panel_topics**: Creates 5 panel ideas with titles and descriptions based on deep context from a TELOS file and input.
-187. **t_find_blindspots**: Identify potential blindspots in thinking, frames, or models that may expose the individual to error or risk.
-188. **t_find_negative_thinking**: Analyze a TELOS file and input to identify negative thinking in documents or journals, followed by tough love encouragement.
-189. **t_find_neglected_goals**: Analyze a TELOS file and input instructions to identify goals or projects that have not been worked on recently.
-190. **t_give_encouragement**: Analyze a TELOS file and input instructions to evaluate progress, provide encouragement, and offer recommendations for continued effort.
-191. **t_red_team_thinking**: Analyze a TELOS file and input instructions to red-team thinking, models, and frames, then provide recommendations for improvement.
-192. **t_threat_model_plans**: Analyze a TELOS file and input instructions to create threat models for a life plan and recommend improvements.
-193. **t_visualize_mission_goals_projects**: Analyze a TELOS file and input instructions to create an ASCII art diagram illustrating the relationship of missions, goals, and projects.
-194. **t_year_in_review**: Analyze a TELOS file to create insights about a person or entity, then summarize accomplishments and visualizations in bullet points.
-195. **to_flashcards**: Create Anki flashcards from a given text, focusing on concise, optimized questions and answers without external context.
-196. **transcribe_minutes**: Extracts (from meeting transcription) meeting minutes, identifying actionables, insightful ideas, decisions, challenges, and next steps in a structured format.
-197. **translate**: Translates sentences or documentation into the specified language code while maintaining the original formatting and tone.
-198. **tweet**: Provides a step-by-step guide on crafting engaging tweets with emojis, covering Twitter basics, account creation, features, and audience targeting.
-199. **write_essay**: Writes concise, clear essays in the style of Paul Graham, focusing on simplicity, clarity, and illumination of the provided topic.
-200. **write_hackerone_report**: Generates concise, clear, and reproducible bug bounty reports, detailing vulnerability impact, steps to reproduce, and exploit details for triagers.
-201. **write_latex**: Generates syntactically correct LaTeX code for a new.tex document, ensuring proper formatting and compatibility with pdflatex.
-202. **write_micro_essay**: Writes concise, clear, and illuminating essays on the given topic in the style of Paul Graham.
-203. **write_nuclei_template_rule**: Generates Nuclei YAML templates for detecting vulnerabilities using HTTP requests, matchers, extractors, and dynamic data extraction.
-204. **write_pull-request**: Drafts detailed pull request descriptions, explaining changes, providing reasoning, and identifying potential bugs from the git diff command output.
-205. **write_semgrep_rule**: Creates accurate and working Semgrep rules based on input, following syntax guidelines and specific language considerations.
-206. **youtube_summary**:  Create concise, timestamped Youtube video summaries that highlight key points.
+3. **analyze_answers**: Evaluate quiz answers for correctness based on learning objectives and generated quiz questions.
+4. **analyze_bill**: Analyzes legislation to identify overt and covert goals, examining bills for hidden agendas and true intentions.
+5. **analyze_bill_short**: Provides a concise analysis of legislation, identifying overt and covert goals in a brief, structured format.
+6. **analyze_candidates**: Compare and contrast two political candidates based on key issues and policies.
+7. **analyze_cfp_submission**: Review and evaluate conference speaking session submissions based on clarity, relevance, depth, and engagement potential.
+8. **analyze_claims**: Analyse and rate truth claims with evidence, counter-arguments, fallacies, and final recommendations.
+9. **analyze_comments**: Evaluate internet comments for content, categorize sentiment, and identify reasons for praise, criticism, and neutrality.
+10. **analyze_debate**: Rate debates on insight, emotionality, and present an unbiased, thorough analysis of arguments, agreements, and disagreements.
+11. **analyze_email_headers**: Provide cybersecurity analysis and actionable insights on SPF, DKIM, DMARC, and ARC email header results.
+12. **analyze_incident**: Efficiently extract and organize key details from cybersecurity breach articles, focusing on attack type, vulnerable components, attacker and target info, incident details, and remediation steps.
+13. **analyze_interviewer_techniques**: This exercise involves analyzing interviewer techniques, identifying their unique qualities, and succinctly articulating what makes them stand out in a clear, simple format.
+14. **analyze_logs**: Analyse server log files to identify patterns, anomalies, and issues, providing data-driven insights and recommendations for improving server reliability and performance.
+15. **analyze_malware**: Analyse malware details, extract key indicators, techniques, and potential detection strategies, and summarize findings concisely for a malware analyst's use in identifying and responding to threats.
+16. **analyze_military_strategy**: Analyse a historical battle, offering in-depth insights into strategic decisions, strengths, weaknesses, tactical approaches, logistical factors, pivotal moments, and consequences for a comprehensive military evaluation.
+17. **analyze_mistakes**: Analyse past mistakes in thinking patterns, map them to current beliefs, and offer recommendations to improve accuracy in predictions.
+18. **analyze_paper**: Analyses research papers by summarizing findings, evaluating rigor, and assessing quality to provide insights for documentation and review.
+19. **analyze_paper_simple**: Analyzes academic papers with a focus on primary findings, research quality, and study design evaluation.
+20. **analyze_patent**: Analyse a patent's field, problem, solution, novelty, inventive step, and advantages in detail while summarizing and extracting keywords.
+21. **analyze_personality**: Performs a deep psychological analysis of a person in the input, focusing on their behavior, language, and psychological traits.
+22. **analyze_presentation**: Reviews and critiques presentations by analyzing the content, speaker's underlying goals, self-focus, and entertainment value.
+23. **analyze_product_feedback**: A prompt for analyzing and organizing user feedback by identifying themes, consolidating similar comments, and prioritizing them based on usefulness.
+24. **analyze_proposition**: Analyzes a ballot proposition by identifying its purpose, impact, arguments for and against, and relevant background information.
+25. **analyze_prose**: Evaluates writing for novelty, clarity, and prose, providing ratings, improvement recommendations, and an overall score.
+26. **analyze_prose_json**: Evaluates writing for novelty, clarity, prose, and provides ratings, explanations, improvement suggestions, and an overall score in a JSON format.
+27. **analyze_prose_pinker**: Evaluates prose based on Steven Pinker's The Sense of Style, analyzing writing style, clarity, and bad writing elements.
+28. **analyze_risk**: Conducts a risk assessment of a third-party vendor, assigning a risk score and suggesting security controls based on analysis of provided documents and vendor website.
+29. **analyze_sales_call**: Rates sales call performance across multiple dimensions, providing scores and actionable feedback based on transcript analysis.
+30. **analyze_spiritual_text**: Compares and contrasts spiritual texts by analyzing claims and differences with the King James Bible.
+31. **analyze_tech_impact**: Analyzes the societal impact, ethical considerations, and sustainability of technology projects, evaluating their outcomes and benefits.
+32. **analyze_terraform_plan**: Analyzes Terraform plan outputs to assess infrastructure changes, security risks, cost implications, and compliance considerations.
+33. **analyze_threat_report**: Extracts surprising insights, trends, statistics, quotes, references, and recommendations from cybersecurity threat reports, summarizing key findings and providing actionable information.
+34. **analyze_threat_report_cmds**: Extract and synthesize actionable cybersecurity commands from provided materials, incorporating command-line arguments and expert insights for pentesters and non-experts.
+35. **analyze_threat_report_trends**: Extract up to 50 surprising, insightful, and interesting trends from a cybersecurity threat report in markdown format.
+36. **answer_interview_question**: Generates concise, tailored responses to technical interview questions, incorporating alternative approaches and evidence to demonstrate the candidate's expertise and experience.
+37. **ask_secure_by_design_questions**: Generates a set of security-focused questions to ensure a project is built securely by design, covering key components and considerations.
+38. **ask_uncle_duke**: Coordinates a team of AI agents to research and produce multiple software development solutions based on provided specifications, and conducts detailed code reviews to ensure adherence to best practices.
+39. **capture_thinkers_work**: Analyze philosophers or philosophies and provide detailed summaries about their teachings, background, works, advice, and related concepts in a structured template.
+40. **check_agreement**: Analyze contracts and agreements to identify important stipulations, issues, and potential gotchas, then summarize them in Markdown.
+41. **clean_text**: Fix broken or malformatted text by correcting line breaks, punctuation, capitalization, and paragraphs without altering content or spelling.
+42. **coding_master**: Explain a coding concept to a beginner, providing examples, and formatting code in markdown with specific output sections like ideas, recommendations, facts, and insights.
+43. **compare_and_contrast**: Compare and contrast a list of items in a markdown table, with items on the left and topics on top.
+44. **convert_to_markdown**: Convert content to clean, complete Markdown format, preserving all original structure, formatting, links, and code blocks without alterations.
+45. **create_5_sentence_summary**: Create concise summaries or answers to input at 5 different levels of depth, from 5 words to 1 word.
+46. **create_academic_paper**: Generate a high-quality academic paper in LaTeX format with clear concepts, structured content, and a professional layout.
+47. **create_ai_jobs_analysis**: Analyze job categories' susceptibility to automation, identify resilient roles, and provide strategies for personal adaptation to AI-driven changes in the workforce.
+48. **create_aphorisms**: Find and generate a list of brief, witty statements.
+49. **create_art_prompt**: Generates a detailed, compelling visual description of a concept, including stylistic references and direct AI instructions for creating art.
+50. **create_better_frame**: Identifies and analyzes different frames of interpreting reality, emphasizing the power of positive, productive lenses in shaping outcomes.
+51. **create_coding_feature**: Generates secure and composable code features using modern technology and best practices from project specifications.
+52. **create_coding_project**: Generate wireframes and starter code for any coding ideas that you have.
+53. **create_command**: Helps determine the correct parameters and switches for penetration testing tools based on a brief description of the objective.
+54. **create_cyber_summary**: Summarizes cybersecurity threats, vulnerabilities, incidents, and malware with a 25-word summary and categorized bullet points, after thoroughly analyzing and mapping the provided input.
+55. **create_design_document**: Creates a detailed design document for a system using the C4 model, addressing business and security postures, and including a system context diagram.
+56. **create_diy**: Creates structured "Do It Yourself" tutorial patterns by analyzing prompts, organizing requirements, and providing step-by-step instructions in Markdown format.
+57. **create_excalidraw_visualization**: Creates complex Excalidraw diagrams to visualize relationships between concepts and ideas in structured format.
+58. **create_flash_cards**: Creates flashcards for key concepts, definitions, and terms with question-answer format for educational purposes.
+59. **create_formal_email**: Crafts professional, clear, and respectful emails by analyzing context, tone, and purpose, ensuring proper structure and formatting.
+60. **create_git_diff_commit**: Generates Git commands and commit messages for reflecting changes in a repository, using conventional commits and providing concise shell commands for updates.
+61. **create_graph_from_input**: Generates a CSV file with progress-over-time data for a security program, focusing on relevant metrics and KPIs.
+62. **create_hormozi_offer**: Creates a customized business offer based on principles from Alex Hormozi's book, "$100M Offers."
+63. **create_idea_compass**: Organizes and structures ideas by exploring their definition, evidence, sources, and related themes or consequences.
+64. **create_investigation_visualization**: Creates detailed Graphviz visualizations of complex input, highlighting key aspects and providing clear, well-annotated diagrams for investigative analysis and conclusions.
+65. **create_keynote**: Creates TED-style keynote presentations with a clear narrative, structured slides, and speaker notes, emphasizing impactful takeaways and cohesive flow.
+66. **create_loe_document**: Creates detailed Level of Effort documents for estimating work effort, resources, and costs for tasks or projects.
+67. **create_logo**: Creates simple, minimalist company logos without text, generating AI prompts for vector graphic logos based on input.
+68. **create_markmap_visualization**: Transforms complex ideas into clear visualizations using MarkMap syntax, simplifying concepts into diagrams with relationships, boxes, arrows, and labels.
+69. **create_mermaid_visualization**: Creates detailed, standalone visualizations of concepts using Mermaid (Markdown) syntax, ensuring clarity and coherence in diagrams.
+70. **create_mermaid_visualization_for_github**: Creates standalone, detailed visualizations using Mermaid (Markdown) syntax to effectively explain complex concepts, ensuring clarity and precision.
+71. **create_micro_summary**: Summarizes content into a concise, 20-word summary with main points and takeaways, formatted in Markdown.
+72. **create_mnemonic_phrases**: Creates memorable mnemonic sentences from given words to aid in memory retention and learning.
+73. **create_network_threat_landscape**: Analyzes open ports and services from a network scan and generates a comprehensive, insightful, and detailed security threat report in Markdown.
+74. **create_newsletter_entry**: Condenses provided article text into a concise, objective, newsletter-style summary with a title in the style of Frontend Weekly.
+75. **create_npc**: Generates a detailed D&D 5E NPC, including background, flaws, stats, appearance, personality, goals, and more in Markdown format.
+76. **create_pattern**: Extracts, organizes, and formats LLM/AI prompts into structured sections, detailing the AI's role, instructions, output format, and any provided examples for clarity and accuracy.
+77. **create_prd**: Creates a precise Product Requirements Document (PRD) in Markdown based on input.
+78. **create_prediction_block**: Extracts and formats predictions from input into a structured Markdown block for a blog post.
+79. **create_quiz**: Creates a three-phase reading plan based on an author or topic to help the user become significantly knowledgeable, including core, extended, and supplementary readings.
+80. **create_reading_plan**: Generates review questions based on learning objectives from the input, adapted to the specified student level, and outputs them in a clear markdown format.
+81. **create_recursive_outline**: Breaks down complex tasks or projects into manageable, hierarchical components with recursive outlining for clarity and simplicity.
+82. **create_report_finding**: Creates a detailed, structured security finding report in markdown, including sections on Description, Risk, Recommendations, References, One-Sentence-Summary, and Quotes.
+83. **create_rpg_summary**: Summarizes an in-person RPG session with key events, combat details, player stats, and role-playing highlights in a structured format.
+84. **create_security_update**: Creates concise security updates for newsletters, covering stories, threats, advisories, vulnerabilities, and a summary of key issues.
+85. **create_show_intro**: Creates compelling short intros for podcasts, summarizing key topics and themes discussed in the episode.
+86. **create_sigma_rules**: Extracts Tactics, Techniques, and Procedures (TTPs) from security news and converts them into Sigma detection rules for host-based detections.
+87. **create_story_explanation**: Summarizes complex content in a clear, approachable story format that makes the concepts easy to understand.
+88. **create_stride_threat_model**: Create a STRIDE-based threat model for a system design, identifying assets, trust boundaries, data flows, and prioritizing threats with mitigations.
+89. **create_summary**: Summarizes content into a 20-word sentence, 10 main points (16 words max), and 5 key takeaways in Markdown format.
+90. **create_tags**: Identifies at least 5 tags from text content for mind mapping tools, including authors and existing tags if present.
+91. **create_threat_scenarios**: Identifies likely attack methods for any system by providing a narrative-based threat model, balancing risk and opportunity.
+92. **create_ttrc_graph**: Creates a CSV file showing the progress of Time to Remediate Critical Vulnerabilities over time using given data.
+93. **create_ttrc_narrative**: Creates a persuasive narrative highlighting progress in reducing the Time to Remediate Critical Vulnerabilities metric over time.
+94. **create_upgrade_pack**: Extracts world model and task algorithm updates from content, providing beliefs about how the world works and task performance.
+95. **create_user_story**: Writes concise and clear technical user stories for new features in complex software programs, formatted for all stakeholders.
+96. **create_video_chapters**: Extracts interesting topics and timestamps from a transcript, providing concise summaries of key moments.
+97. **create_visualization**: Transforms complex ideas into visualizations using intricate ASCII art, simplifying concepts where necessary.
+98. **dialog_with_socrates**: Engages in deep, meaningful dialogues to explore and challenge beliefs using the Socratic method.
+99. **enrich_blog_post**: Enhances Markdown blog files by applying instructions to improve structure, visuals, and readability for HTML rendering.
+100. **explain_code**: Explains code, security tool output, configuration text, and answers questions based on the provided input.
+101. **explain_docs**: Improves and restructures tool documentation into clear, concise instructions, including overviews, usage, use cases, and key features.
+102. **explain_math**: Helps you understand mathematical concepts in a clear and engaging way.
+103. **explain_project**: Summarizes project documentation into clear, concise sections covering the project, problem, solution, installation, usage, and examples.
+104. **explain_terms**: Produces a glossary of advanced terms from content, providing a definition, analogy, and explanation of why each term matters.
+105. **export_data_as_csv**: Extracts and outputs all data structures from the input in properly formatted CSV data.
+106. **extract_algorithm_update_recommendations**: Extracts concise, practical algorithm update recommendations from the input and outputs them in a bulleted list.
+107. **extract_article_wisdom**: Extracts surprising, insightful, and interesting information from content, categorizing it into sections like summary, ideas, quotes, facts, references, and recommendations.
+108. **extract_book_ideas**: Extracts and outputs 50 to 100 of the most surprising, insightful, and interesting ideas from a book's content.
+109. **extract_book_recommendations**: Extracts and outputs 50 to 100 practical, actionable recommendations from a book's content.
+110. **extract_business_ideas**: Extracts top business ideas from content and elaborates on the best 10 with unique differentiators.
+111. **extract_controversial_ideas**: Extracts and outputs controversial statements and supporting quotes from the input in a structured Markdown list.
+112. **extract_core_message**: Extracts and outputs a clear, concise sentence that articulates the core message of a given text or body of work.
+113. **extract_ctf_writeup**: Extracts a short writeup from a warstory-like text about a cyber security engagement.
+114. **extract_domains**: Extracts domains and URLs from content to identify sources used for articles, newsletters, and other publications.
+115. **extract_extraordinary_claims**: Extracts and outputs a list of extraordinary claims from conversations, focusing on scientifically disputed or false statements.
+116. **extract_ideas**: Extracts and outputs all the key ideas from input, presented as 15-word bullet points in Markdown.
+117. **extract_insights**: Extracts and outputs the most powerful and insightful ideas from text, formatted as 16-word bullet points in the INSIGHTS section, also IDEAS section.
+118. **extract_insights_dm**: Extracts and outputs all valuable insights and a concise summary of the content, including key points and topics discussed.
+119. **extract_instructions**: Extracts clear, actionable step-by-step instructions and main objectives from instructional video transcripts, organizing them into a concise list.
+120. **extract_jokes**: Extracts jokes from text content, presenting each joke with its punchline in separate bullet points.
+121. **extract_latest_video**: Extracts the latest video URL from a YouTube RSS feed and outputs the URL only.
+122. **extract_main_activities**: Extracts key events and activities from transcripts or logs, providing a summary of what happened.
+123. **extract_main_idea**: Extracts the main idea and key recommendation from the input, summarizing them in 15-word sentences.
+124. **extract_most_redeeming_thing**: Extracts the most redeeming aspect from an input, summarizing it in a single 15-word sentence.
+125. **extract_patterns**: Extracts and analyzes recurring, surprising, and insightful patterns from input, providing detailed analysis and advice for builders.
+126. **extract_poc**: Extracts proof of concept URLs and validation methods from security reports, providing the URL and command to run.
+127. **extract_predictions**: Extracts predictions from input, including specific details such as date, confidence level, and verification method.
+128. **extract_primary_problem**: Extracts the primary problem with the world as presented in a given text or body of work.
+129. **extract_primary_solution**: Extracts the primary solution for the world as presented in a given text or body of work.
+130. **extract_product_features**: Extracts and outputs a list of product features from the provided input in a bulleted format.
+131. **extract_questions**: Extracts and outputs all questions asked by the interviewer in a conversation or interview.
+132. **extract_recipe**: Extracts and outputs a recipe with a short meal description, ingredients with measurements, and preparation steps.
+133. **extract_recommendations**: Extracts and outputs concise, practical recommendations from a given piece of content in a bulleted list.
+134. **extract_references**: Extracts and outputs a bulleted list of references to art, stories, books, literature, and other sources from content.
+135. **extract_skills**: Extracts and classifies skills from a job description into a table, separating each skill and classifying it as either hard or soft.
+136. **extract_song_meaning**: Analyzes a song to provide a summary of its meaning, supported by detailed evidence from lyrics, artist commentary, and fan analysis.
+137. **extract_sponsors**: Extracts and lists official sponsors and potential sponsors from a provided transcript.
+138. **extract_videoid**: Extracts and outputs the video ID from any given URL.
+139. **extract_wisdom**: Extracts surprising, insightful, and interesting information from text on topics like human flourishing, AI, learning, and more.
+140. **extract_wisdom_agents**: Extracts valuable insights, ideas, quotes, and references from content, emphasizing topics like human flourishing, AI, learning, and technology.
+141. **extract_wisdom_dm**: Extracts all valuable, insightful, and thought-provoking information from content, focusing on topics like human flourishing, AI, learning, and technology.
+142. **extract_wisdom_nometa**: Extracts insights, ideas, quotes, habits, facts, references, and recommendations from content, focusing on human flourishing, AI, technology, and related topics.
+143. **find_female_life_partner**: Analyzes criteria for finding a female life partner and provides clear, direct, and poetic descriptions.
+144. **find_hidden_message**: Extracts overt and hidden political messages, justifications, audience actions, and a cynical analysis from content.
+145. **find_logical_fallacies**: Identifies and analyzes fallacies in arguments, classifying them as formal or informal with detailed reasoning.
+146. **get_wow_per_minute**: Determines the wow-factor of content per minute based on surprise, novelty, insight, value, and wisdom, measuring how rewarding the content is for the viewer.
+147. **get_youtube_rss**: Returns the RSS URL for a given YouTube channel based on the channel ID or URL.
+148. **humanize**: Rewrites AI-generated text to sound natural, conversational, and easy to understand, maintaining clarity and simplicity.
+149. **identify_dsrp_distinctions**: Encourages creative, systems-based thinking by exploring distinctions, boundaries, and their implications, drawing on insights from prominent systems thinkers.
+150. **identify_dsrp_perspectives**: Explores the concept of distinctions in systems thinking, focusing on how boundaries define ideas, influence understanding, and reveal or obscure insights.
+151. **identify_dsrp_relationships**: Encourages exploration of connections, distinctions, and boundaries between ideas, inspired by systems thinkers to reveal new insights and patterns in complex systems.
+152. **identify_dsrp_systems**: Encourages organizing ideas into systems of parts and wholes, inspired by systems thinkers to explore relationships and how changes in organization impact meaning and understanding.
+153. **identify_job_stories**: Identifies key job stories or requirements for roles.
+154. **improve_academic_writing**: Refines text into clear, concise academic language while improving grammar, coherence, and clarity, with a list of changes.
+155. **improve_prompt**: Improves an LLM/AI prompt by applying expert prompt writing strategies for better results and clarity.
+156. **improve_report_finding**: Improves a penetration test security finding by providing detailed descriptions, risks, recommendations, references, quotes, and a concise summary in markdown format.
+157. **improve_writing**: Refines text by correcting grammar, enhancing style, improving clarity, and maintaining the original meaning. skills.
+158. **judge_output**: Evaluates Honeycomb queries by judging their effectiveness, providing critiques and outcomes based on language nuances and analytics relevance.
+159. **label_and_rate**: Labels content with up to 20 single-word tags and rates it based on idea count and relevance to human meaning, AI, and other related themes, assigning a tier (S, A, B, C, D) and a quality score.
+160. **md_callout**: Classifies content and generates a markdown callout based on the provided text, selecting the most appropriate type.
+161. **official_pattern_template**: Template to use if you want to create new fabric patterns.
+162. **prepare_7s_strategy**: Prepares a comprehensive briefing document from 7S's strategy capturing organizational profile, strategic elements, and market dynamics with clear, concise, and organized content.
+163. **provide_guidance**: Provides psychological and life coaching advice, including analysis, recommendations, and potential diagnoses, with a compassionate and honest tone.
+164. **rate_ai_response**: Rates the quality of AI responses by comparing them to top human expert performance, assigning a letter grade, reasoning, and providing a 1-100 score based on the evaluation.
+165. **rate_ai_result**: Assesses the quality of AI/ML/LLM work by deeply analyzing content, instructions, and output, then rates performance based on multiple dimensions, including coverage, creativity, and interdisciplinary thinking.
+166. **rate_content**: Labels content with up to 20 single-word tags and rates it based on idea count and relevance to human meaning, AI, and other related themes, assigning a tier (S, A, B, C, D) and a quality score.
+167. **rate_value**: Produces the best possible output by deeply analyzing and understanding the input and its intended purpose.
+168. **raw_query**: Fully digests and contemplates the input to produce the best possible result based on understanding the sender's intent.
+169. **recommend_artists**: Recommends a personalized festival schedule with artists aligned to your favorite styles and interests, including rationale.
+170. **recommend_pipeline_upgrades**: Optimizes vulnerability-checking pipelines by incorporating new information and improving their efficiency, with detailed explanations of changes.
+171. **recommend_talkpanel_topics**: Produces a clean set of proposed talks or panel talking points for a person based on their interests and goals, formatted for submission to a conference organizer.
+172. **refine_design_document**: Refines a design document based on a design review by analyzing, mapping concepts, and implementing changes using valid Markdown.
+173. **review_design**: Reviews and analyzes architecture design, focusing on clarity, component design, system integrations, security, performance, scalability, and data management.
+174. **sanitize_broken_html_to_markdown**: Converts messy HTML into clean, properly formatted Markdown, applying custom styling and ensuring compatibility with Vite.
+175. **show_fabric_options_markmap**: Visualizes the functionality of the Fabric framework by representing its components, commands, and features based on the provided input.
+176. **solve_with_cot**: Provides detailed, step-by-step responses with chain of thought reasoning, using structured thinking, reflection, and output sections.
+177. **suggest_pattern**: Suggests appropriate fabric patterns or commands based on user input, providing clear explanations and options for users.
+178. **summarize**: Summarizes content into a 20-word sentence, main points, and takeaways, formatted with numbered lists in Markdown.
+179. **summarize_board_meeting**: Creates formal meeting notes from board meeting transcripts for corporate governance documentation.
+180. **summarize_debate**: Summarizes debates, identifies primary disagreement, extracts arguments, and provides analysis of evidence and argument strength to predict outcomes.
+181. **summarize_git_changes**: Summarizes recent project updates from the last 7 days, focusing on key changes with enthusiasm.
+182. **summarize_git_diff**: Summarizes and organizes Git diff changes with clear, succinct commit messages and bullet points.
+183. **summarize_lecture**: Extracts relevant topics, definitions, and tools from lecture transcripts, providing structured summaries with timestamps and key takeaways.
+184. **summarize_legislation**: Summarizes complex political proposals and legislation by analyzing key points, proposed changes, and providing balanced, positive, and cynical characterizations.
+185. **summarize_meeting**: Analyzes meeting transcripts to extract a structured summary, including an overview, key points, tasks, decisions, challenges, timeline, references, and next steps.
+186. **summarize_micro**: Summarizes content into a 20-word sentence, 3 main points, and 3 takeaways, formatted in clear, concise Markdown.
+187. **summarize_newsletter**: Extracts the most meaningful, interesting, and useful content from a newsletter, summarizing key sections such as content, opinions, tools, companies, and follow-up items in clear, structured Markdown.
+188. **summarize_paper**: Summarizes an academic paper by detailing its title, authors, technical approach, distinctive features, experimental setup, results, advantages, limitations, and conclusion in a clear, structured format using human-readable Markdown.
+189. **summarize_prompt**: Summarizes AI chat prompts by describing the primary function, unique approach, and expected output in a concise paragraph. The summary is focused on the prompt's purpose without unnecessary details or formatting.
+190. **summarize_pull-requests**: Summarizes pull requests for a coding project by providing a summary and listing the top PRs with human-readable descriptions.
+191. **summarize_rpg_session**: Summarizes a role-playing game session by extracting key events, combat stats, character changes, quotes, and more.
+192. **t_analyze_challenge_handling**: Provides 8-16 word bullet points evaluating how well challenges are being addressed, calling out any lack of effort.
+193. **t_check_metrics**: Analyzes deep context from the TELOS file and input instruction, then provides a wisdom-based output while considering metrics and KPIs to assess recent improvements.
+194. **t_create_h3_career**: Summarizes context and produces wisdom-based output by deeply analyzing both the TELOS File and the input instruction, considering the relationship between the two.
+195. **t_create_opening_sentences**: Describes from TELOS file the person's identity, goals, and actions in 4 concise, 32-word bullet points, humbly.
+196. **t_describe_life_outlook**: Describes from TELOS file a person's life outlook in 5 concise, 16-word bullet points.
+197. **t_extract_intro_sentences**: Summarizes from TELOS file a person's identity, work, and current projects in 5 concise and grounded bullet points.
+198. **t_extract_panel_topics**: Creates 5 panel ideas with titles and descriptions based on deep context from a TELOS file and input.
+199. **t_find_blindspots**: Identify potential blindspots in thinking, frames, or models that may expose the individual to error or risk.
+200. **t_find_negative_thinking**: Analyze a TELOS file and input to identify negative thinking in documents or journals, followed by tough love encouragement.
+201. **t_find_neglected_goals**: Analyze a TELOS file and input instructions to identify goals or projects that have not been worked on recently.
+202. **t_give_encouragement**: Analyze a TELOS file and input instructions to evaluate progress, provide encouragement, and offer recommendations for continued effort.
+203. **t_red_team_thinking**: Analyze a TELOS file and input instructions to red-team thinking, models, and frames, then provide recommendations for improvement.
+204. **t_threat_model_plans**: Analyze a TELOS file and input instructions to create threat models for a life plan and recommend improvements.
+205. **t_visualize_mission_goals_projects**: Analyze a TELOS file and input instructions to create an ASCII art diagram illustrating the relationship of missions, goals, and projects.
+206. **t_year_in_review**: Analyze a TELOS file to create insights about a person or entity, then summarize accomplishments and visualizations in bullet points.
+207. **to_flashcards**: Create Anki flashcards from a given text, focusing on concise, optimized questions and answers without external context.
+208. **transcribe_minutes**: Extracts (from meeting transcription) meeting minutes, identifying actionables, insightful ideas, decisions, challenges, and next steps in a structured format.
+209. **translate**: Translates sentences or documentation into the specified language code while maintaining the original formatting and tone.
+210. **tweet**: Provides a step-by-step guide on crafting engaging tweets with emojis, covering Twitter basics, account creation, features, and audience targeting.
+211. **write_essay**: Writes essays in the style of a specified author, embodying their unique voice, vocabulary, and approach. Uses `author_name` variable.
+212. **write_essay_pg**: Writes concise, clear essays in the style of Paul Graham, focusing on simplicity, clarity, and illumination of the provided topic.
+213. **write_hackerone_report**: Generates concise, clear, and reproducible bug bounty reports, detailing vulnerability impact, steps to reproduce, and exploit details for triagers.
+214. **write_latex**: Generates syntactically correct LaTeX code for a new.tex document, ensuring proper formatting and compatibility with pdflatex.
+215. **write_micro_essay**: Writes concise, clear, and illuminating essays on the given topic in the style of Paul Graham.
+216. **write_nuclei_template_rule**: Generates Nuclei YAML templates for detecting vulnerabilities using HTTP requests, matchers, extractors, and dynamic data extraction.
+217. **write_pull-request**: Drafts detailed pull request descriptions, explaining changes, providing reasoning, and identifying potential bugs from the git diff command output.
+218. **write_semgrep_rule**: Creates accurate and working Semgrep rules based on input, following syntax guidelines and specific language considerations.
+219. **youtube_summary**: Create concise, timestamped Youtube video summaries that highlight key points.

patterns/raycast/capture_thinkers_work

@@ -1,27 +0,0 @@
-#!/bin/bash
-
-# Required parameters:
-# @raycast.schemaVersion 1
-# @raycast.title Capture Thinkers Work
-# @raycast.mode fullOutput
-
-# Optional parameters:
-# @raycast.icon 🧠
-# @raycast.argument1 { "type": "text", "placeholder": "Input text", "optional": false, "percentEncoded": true}
-
-# Documentation:
-# @raycast.description Run fabric capture_thinkers_work on the input text
-# @raycast.author Daniel Miessler
-# @raycast.authorURL https://github.com/danielmiessler
-
-# Set PATH to include common locations and $HOME/go/bin
-PATH="/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin:$HOME/go/bin:$PATH"
-
-# Use the PATH to find and execute fabric
-if command -v fabric >/dev/null 2>&1; then
-    fabric -sp capture_thinkers_work "${1}"
-else
-    echo "Error: fabric command not found in PATH"
-    echo "Current PATH: $PATH"
-    exit 1
-fi

patterns/raycast/create_story_explanation

@@ -1,27 +0,0 @@
-#!/bin/bash
-
-# Required parameters:
-# @raycast.schemaVersion 1
-# @raycast.title Create Story Explanation
-# @raycast.mode fullOutput
-
-# Optional parameters:
-# @raycast.icon 🧠
-# @raycast.argument1 { "type": "text", "placeholder": "Input text", "optional": false, "percentEncoded": true}
-
-# Documentation:
-# @raycast.description Run fabric create_story_explanation on the input text
-# @raycast.author Daniel Miessler
-# @raycast.authorURL https://github.com/danielmiessler
-
-# Set PATH to include common locations and $HOME/go/bin
-PATH="/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin:$HOME/go/bin:$PATH"
-
-# Use the PATH to find and execute fabric
-if command -v fabric >/dev/null 2>&1; then
-    fabric -sp create_story_explanation "${1}"
-else
-    echo "Error: fabric command not found in PATH"
-    echo "Current PATH: $PATH"
-    exit 1
-fi

patterns/raycast/extract_primary_problem

@@ -1,27 +0,0 @@
-#!/bin/bash
-
-# Required parameters:
-# @raycast.schemaVersion 1
-# @raycast.title Extract Primary Problem
-# @raycast.mode fullOutput
-
-# Optional parameters:
-# @raycast.icon 🧠
-# @raycast.argument1 { "type": "text", "placeholder": "Input text", "optional": false, "percentEncoded": true}
-
-# Documentation:
-# @raycast.description Run fabric extract_primary_problem on the input text
-# @raycast.author Daniel Miessler
-# @raycast.authorURL https://github.com/danielmiessler
-
-# Set PATH to include common locations and $HOME/go/bin
-PATH="/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin:$HOME/go/bin:$PATH"
-
-# Use the PATH to find and execute fabric
-if command -v fabric >/dev/null 2>&1; then
-    fabric -sp extract_primary_problem "${1}"
-else
-    echo "Error: fabric command not found in PATH"
-    echo "Current PATH: $PATH"
-    exit 1
-fi

patterns/raycast/extract_wisdom

@@ -1,27 +0,0 @@
-#!/bin/bash
-
-# Required parameters:
-# @raycast.schemaVersion 1
-# @raycast.title Extract Wisdom
-# @raycast.mode fullOutput
-
-# Optional parameters:
-# @raycast.icon 🧠
-# @raycast.argument1 { "type": "text", "placeholder": "Input text", "optional": false, "percentEncoded": true}
-
-# Documentation:
-# @raycast.description Run fabric extract_wisdom on input text
-# @raycast.author Daniel Miessler
-# @raycast.authorURL https://github.com/danielmiessler
-
-# Set PATH to include common locations and $HOME/go/bin
-PATH="/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin:$HOME/go/bin:$PATH"
-
-# Use the PATH to find and execute fabric
-if command -v fabric >/dev/null 2>&1; then
-    fabric -sp extract_wisdom "${1}"
-else
-    echo "Error: fabric command not found in PATH"
-    echo "Current PATH: $PATH"
-    exit 1
-fi

patterns/raycast/yt

@@ -1,27 +0,0 @@
-#!/bin/bash
-
-# Required parameters:
-# @raycast.schemaVersion 1
-# @raycast.title Get YouTube Transcript
-# @raycast.mode fullOutput
-
-# Optional parameters:
-# @raycast.icon 🧠
-# @raycast.argument1 { "type": "text", "placeholder": "Input text", "optional": false, "percentEncoded": false}
-
-# Documentation:
-# @raycast.description Run fabric -y on the input text of a YouTube video to get the transcript from.
-# @raycast.author Daniel Miessler
-# @raycast.authorURL https://github.com/danielmiessler
-
-# Set PATH to include common locations and $HOME/go/bin
-PATH="/usr/local/bin:/usr/bin:/bin:/usr/sbin:/sbin:$HOME/go/bin:$PATH"
-
-# Use the PATH to find and execute fabric
-if command -v fabric >/dev/null 2>&1; then
-    fabric -y "${1}"
-else
-    echo "Error: fabric command not found in PATH"
-    echo "Current PATH: $PATH"
-    exit 1
-fi

patterns/suggest_pattern/user_updated.md

@@ -0,0 +1,919 @@
+# Suggest Pattern
+
+## OVERVIEW
+
+What It Does: Fabric is an open-source framework designed to augment human capabilities using AI, making it easier to integrate AI into daily tasks.
+
+Why People Use It: Users leverage Fabric to seamlessly apply AI for solving everyday challenges, enhancing productivity, and fostering human creativity through technology.
+
+## HOW TO USE IT
+
+Most Common Syntax: The most common usage involves executing Fabric commands in the terminal, such as `fabric --pattern <PATTERN_NAME>`.
+
+## COMMON USE CASES
+
+For Summarizing Content: `fabric --pattern summarize`
+For Analyzing Claims: `fabric --pattern analyze_claims`
+For Extracting Wisdom from Videos: `fabric --pattern extract_wisdom`
+For creating custom patterns: `fabric --pattern create_pattern`
+
+- One possible place to store them is ~/.config/custom-fabric-patterns.
+- Then when you want to use them, simply copy them into ~/.config/fabric/patterns.
+`cp -a ~/.config/custom-fabric-patterns/* ~/.config/fabric/patterns/`
+- Now you can run them with: `pbpaste | fabric -p your_custom_pattern`
+
+## MOST IMPORTANT AND USED OPTIONS AND FEATURES
+
+- **--pattern PATTERN, -p PATTERN**: Specifies the pattern (prompt) to use. Useful for applying specific AI prompts to your input.
+
+- **--stream, -s**: Streams results in real-time. Ideal for getting immediate feedback from AI operations.
+
+- **--update, -u**: Updates patterns. Ensures you're using the latest AI prompts for your tasks.
+
+- **--model MODEL, -m MODEL**: Selects the AI model to use. Allows customization of the AI backend for different tasks.
+
+- **--setup, -S**: Sets up your Fabric instance. Essential for first-time users to configure Fabric correctly.
+
+- **--list, -l**: Lists available patterns. Helps users discover new AI prompts for various applications.
+
+- **--context, -C**: Uses a Context file to add context to your pattern. Enhances the relevance of AI responses by providing additional background information.
+
+## PATTERNS
+
+**Key pattern to use: `suggest_pattern`** - suggests appropriate fabric patterns or commands based on user input.
+
+### agility_story
+
+Generate a user story and acceptance criteria in JSON format based on the given topic.
+
+### ai
+
+Interpret questions deeply and provide concise, insightful answers in Markdown bullet points.
+
+### analyze_answers
+
+Evaluate quiz answers for correctness based on learning objectives and generated quiz questions.
+
+### analyze_bill
+
+Analyzes legislation to identify overt and covert goals, examining bills for hidden agendas and true intentions.
+
+### analyze_bill_short
+
+Provides a concise analysis of legislation, identifying overt and covert goals in a brief, structured format.
+
+### analyze_candidates
+
+Compare and contrast two political candidates based on key issues and policies.
+
+### analyze_cfp_submission
+
+Review and evaluate conference speaking session submissions based on clarity, relevance, depth, and engagement potential.
+
+### analyze_claims
+
+Analyse and rate truth claims with evidence, counter-arguments, fallacies, and final recommendations.
+
+### analyze_comments
+
+Evaluate internet comments for content, categorize sentiment, and identify reasons for praise, criticism, and neutrality.
+
+### analyze_debate
+
+Rate debates on insight, emotionality, and present an unbiased, thorough analysis of arguments, agreements, and disagreements.
+
+### analyze_email_headers
+
+Provide cybersecurity analysis and actionable insights on SPF, DKIM, DMARC, and ARC email header results.
+
+### analyze_incident
+
+Efficiently extract and organize key details from cybersecurity breach articles, focusing on attack type, vulnerable components, attacker and target info, incident details, and remediation steps.
+
+### analyze_interviewer_techniques
+
+This exercise involves analyzing interviewer techniques, identifying their unique qualities, and succinctly articulating what makes them stand out in a clear, simple format.
+
+### analyze_logs
+
+Analyse server log files to identify patterns, anomalies, and issues, providing data-driven insights and recommendations for improving server reliability and performance.
+
+### analyze_malware
+
+Analyse malware details, extract key indicators, techniques, and potential detection strategies, and summarize findings concisely for a malware analyst's use in identifying and responding to threats.
+
+### analyze_military_strategy
+
+Analyse a historical battle, offering in-depth insights into strategic decisions, strengths, weaknesses, tactical approaches, logistical factors, pivotal moments, and consequences for a comprehensive military evaluation.
+
+### analyze_mistakes
+
+Analyse past mistakes in thinking patterns, map them to current beliefs, and offer recommendations to improve accuracy in predictions.
+
+### analyze_paper
+
+Analyses research papers by summarizing findings, evaluating rigor, and assessing quality to provide insights for documentation and review.
+
+### analyze_paper_simple
+
+Analyzes academic papers with a focus on primary findings, research quality, and study design evaluation.
+
+### analyze_patent
+
+Analyse a patent's field, problem, solution, novelty, inventive step, and advantages in detail while summarizing and extracting keywords.
+
+### analyze_personality
+
+Performs a deep psychological analysis of a person in the input, focusing on their behavior, language, and psychological traits.
+
+### analyze_presentation
+
+Reviews and critiques presentations by analyzing the content, speaker's underlying goals, self-focus, and entertainment value.
+
+### analyze_product_feedback
+
+A prompt for analyzing and organizing user feedback by identifying themes, consolidating similar comments, and prioritizing them based on usefulness.
+
+### analyze_proposition
+
+Analyzes a ballot proposition by identifying its purpose, impact, arguments for and against, and relevant background information.
+
+### analyze_prose
+
+Evaluates writing for novelty, clarity, and prose, providing ratings, improvement recommendations, and an overall score.
+
+### analyze_prose_json
+
+Evaluates writing for novelty, clarity, prose, and provides ratings, explanations, improvement suggestions, and an overall score in a JSON format.
+
+### analyze_prose_pinker
+
+Evaluates prose based on Steven Pinker's The Sense of Style, analyzing writing style, clarity, and bad writing elements.
+
+### analyze_risk
+
+Conducts a risk assessment of a third-party vendor, assigning a risk score and suggesting security controls based on analysis of provided documents and vendor website.
+
+### analyze_sales_call
+
+Rates sales call performance across multiple dimensions, providing scores and actionable feedback based on transcript analysis.
+
+### analyze_spiritual_text
+
+Compares and contrasts spiritual texts by analyzing claims and differences with the King James Bible.
+
+### analyze_tech_impact
+
+Analyzes the societal impact, ethical considerations, and sustainability of technology projects, evaluating their outcomes and benefits.
+
+### analyze_terraform_plan
+
+Analyzes Terraform plan outputs to assess infrastructure changes, security risks, cost implications, and compliance considerations.
+
+### analyze_threat_report
+
+Extracts surprising insights, trends, statistics, quotes, references, and recommendations from cybersecurity threat reports, summarizing key findings and providing actionable information.
+
+### analyze_threat_report_cmds
+
+Extract and synthesize actionable cybersecurity commands from provided materials, incorporating command-line arguments and expert insights for pentesters and non-experts.
+
+### analyze_threat_report_trends
+
+Extract up to 50 surprising, insightful, and interesting trends from a cybersecurity threat report in markdown format.
+
+### answer_interview_question
+
+Generates concise, tailored responses to technical interview questions, incorporating alternative approaches and evidence to demonstrate the candidate's expertise and experience.
+
+### ask_secure_by_design_questions
+
+Generates a set of security-focused questions to ensure a project is built securely by design, covering key components and considerations.
+
+### ask_uncle_duke
+
+Coordinates a team of AI agents to research and produce multiple software development solutions based on provided specifications, and conducts detailed code reviews to ensure adherence to best practices.
+
+### capture_thinkers_work
+
+Analyze philosophers or philosophies and provide detailed summaries about their teachings, background, works, advice, and related concepts in a structured template.
+
+### check_agreement
+
+Analyze contracts and agreements to identify important stipulations, issues, and potential gotchas, then summarize them in Markdown.
+
+### clean_text
+
+Fix broken or malformatted text by correcting line breaks, punctuation, capitalization, and paragraphs without altering content or spelling.
+
+### coding_master
+
+Explain a coding concept to a beginner, providing examples, and formatting code in markdown with specific output sections like ideas, recommendations, facts, and insights.
+
+### compare_and_contrast
+
+Compare and contrast a list of items in a markdown table, with items on the left and topics on top.
+
+### convert_to_markdown
+
+Convert content to clean, complete Markdown format, preserving all original structure, formatting, links, and code blocks without alterations.
+
+### create_5_sentence_summary
+
+Create concise summaries or answers to input at 5 different levels of depth, from 5 words to 1 word.
+
+### create_academic_paper
+
+Generate a high-quality academic paper in LaTeX format with clear concepts, structured content, and a professional layout.
+
+### create_ai_jobs_analysis
+
+Analyze job categories' susceptibility to automation, identify resilient roles, and provide strategies for personal adaptation to AI-driven changes in the workforce.
+
+### create_aphorisms
+
+Find and generate a list of brief, witty statements.
+
+### create_art_prompt
+
+Generates a detailed, compelling visual description of a concept, including stylistic references and direct AI instructions for creating art.
+
+### create_better_frame
+
+Identifies and analyzes different frames of interpreting reality, emphasizing the power of positive, productive lenses in shaping outcomes.
+
+### create_coding_feature
+
+Generates secure and composable code features using modern technology and best practices from project specifications.
+
+### create_coding_project
+
+Generate wireframes and starter code for any coding ideas that you have.
+
+### create_command
+
+Helps determine the correct parameters and switches for penetration testing tools based on a brief description of the objective.
+
+### create_cyber_summary
+
+Summarizes cybersecurity threats, vulnerabilities, incidents, and malware with a 25-word summary and categorized bullet points, after thoroughly analyzing and mapping the provided input.
+
+### create_design_document
+
+Creates a detailed design document for a system using the C4 model, addressing business and security postures, and including a system context diagram.
+
+### create_diy
+
+Creates structured "Do It Yourself" tutorial patterns by analyzing prompts, organizing requirements, and providing step-by-step instructions in Markdown format.
+
+### create_excalidraw_visualization
+
+Creates complex Excalidraw diagrams to visualize relationships between concepts and ideas in structured format.
+
+### create_flash_cards
+
+Creates flashcards for key concepts, definitions, and terms with question-answer format for educational purposes.
+
+### create_formal_email
+
+Crafts professional, clear, and respectful emails by analyzing context, tone, and purpose, ensuring proper structure and formatting.
+
+### create_git_diff_commit
+
+Generates Git commands and commit messages for reflecting changes in a repository, using conventional commits and providing concise shell commands for updates.
+
+### create_graph_from_input
+
+Generates a CSV file with progress-over-time data for a security program, focusing on relevant metrics and KPIs.
+
+### create_hormozi_offer
+
+Creates a customized business offer based on principles from Alex Hormozi's book, "$100M Offers."
+
+### create_idea_compass
+
+Organizes and structures ideas by exploring their definition, evidence, sources, and related themes or consequences.
+
+### create_investigation_visualization
+
+Creates detailed Graphviz visualizations of complex input, highlighting key aspects and providing clear, well-annotated diagrams for investigative analysis and conclusions.
+
+### create_keynote
+
+Creates TED-style keynote presentations with a clear narrative, structured slides, and speaker notes, emphasizing impactful takeaways and cohesive flow.
+
+### create_loe_document
+
+Creates detailed Level of Effort documents for estimating work effort, resources, and costs for tasks or projects.
+
+### create_logo
+
+Creates simple, minimalist company logos without text, generating AI prompts for vector graphic logos based on input.
+
+### create_markmap_visualization
+
+Transforms complex ideas into clear visualizations using MarkMap syntax, simplifying concepts into diagrams with relationships, boxes, arrows, and labels.
+
+### create_mermaid_visualization
+
+Creates detailed, standalone visualizations of concepts using Mermaid (Markdown) syntax, ensuring clarity and coherence in diagrams.
+
+### create_mermaid_visualization_for_github
+
+Creates standalone, detailed visualizations using Mermaid (Markdown) syntax to effectively explain complex concepts, ensuring clarity and precision.
+
+### create_micro_summary
+
+Summarizes content into a concise, 20-word summary with main points and takeaways, formatted in Markdown.
+
+### create_mnemonic_phrases
+
+Creates memorable mnemonic sentences from given words to aid in memory retention and learning.
+
+### create_network_threat_landscape
+
+Analyzes open ports and services from a network scan and generates a comprehensive, insightful, and detailed security threat report in Markdown.
+
+### create_newsletter_entry
+
+Condenses provided article text into a concise, objective, newsletter-style summary with a title in the style of Frontend Weekly.
+
+### create_npc
+
+Generates a detailed D&D 5E NPC, including background, flaws, stats, appearance, personality, goals, and more in Markdown format.
+
+### create_pattern
+
+Extracts, organizes, and formats LLM/AI prompts into structured sections, detailing the AI's role, instructions, output format, and any provided examples for clarity and accuracy.
+
+### create_prd
+
+Creates a precise Product Requirements Document (PRD) in Markdown based on input.
+
+### create_prediction_block
+
+Extracts and formats predictions from input into a structured Markdown block for a blog post.
+
+### create_quiz
+
+Generates review questions based on learning objectives from the input, adapted to the specified student level, and outputs them in a clear markdown format.
+
+### create_reading_plan
+
+Creates a three-phase reading plan based on an author or topic to help the user become significantly knowledgeable, including core, extended, and supplementary readings.
+
+### create_recursive_outline
+
+Breaks down complex tasks or projects into manageable, hierarchical components with recursive outlining for clarity and simplicity.
+
+### create_report_finding
+
+Creates a detailed, structured security finding report in markdown, including sections on Description, Risk, Recommendations, References, One-Sentence-Summary, and Quotes.
+
+### create_rpg_summary
+
+Summarizes an in-person RPG session with key events, combat details, player stats, and role-playing highlights in a structured format.
+
+### create_security_update
+
+Creates concise security updates for newsletters, covering stories, threats, advisories, vulnerabilities, and a summary of key issues.
+
+### create_show_intro
+
+Creates compelling short intros for podcasts, summarizing key topics and themes discussed in the episode.
+
+### create_sigma_rules
+
+Extracts Tactics, Techniques, and Procedures (TTPs) from security news and converts them into Sigma detection rules for host-based detections.
+
+### create_story_explanation
+
+Summarizes complex content in a clear, approachable story format that makes the concepts easy to understand.
+
+### create_stride_threat_model
+
+Create a STRIDE-based threat model for a system design, identifying assets, trust boundaries, data flows, and prioritizing threats with mitigations.
+
+### create_summary
+
+Summarizes content into a 20-word sentence, 10 main points (16 words max), and 5 key takeaways in Markdown format.
+
+### create_tags
+
+Identifies at least 5 tags from text content for mind mapping tools, including authors and existing tags if present.
+
+### create_threat_scenarios
+
+Identifies likely attack methods for any system by providing a narrative-based threat model, balancing risk and opportunity.
+
+### create_ttrc_graph
+
+Creates a CSV file showing the progress of Time to Remediate Critical Vulnerabilities over time using given data.
+
+### create_ttrc_narrative
+
+Creates a persuasive narrative highlighting progress in reducing the Time to Remediate Critical Vulnerabilities metric over time.
+
+### create_upgrade_pack
+
+Extracts world model and task algorithm updates from content, providing beliefs about how the world works and task performance.
+
+### create_user_story
+
+Writes concise and clear technical user stories for new features in complex software programs, formatted for all stakeholders.
+
+### create_video_chapters
+
+Extracts interesting topics and timestamps from a transcript, providing concise summaries of key moments.
+
+### create_visualization
+
+Transforms complex ideas into visualizations using intricate ASCII art, simplifying concepts where necessary.
+
+### dialog_with_socrates
+
+Engages in deep, meaningful dialogues to explore and challenge beliefs using the Socratic method.
+
+### enrich_blog_post
+
+Enhances Markdown blog files by applying instructions to improve structure, visuals, and readability for HTML rendering.
+
+### explain_code
+
+Explains code, security tool output, configuration text, and answers questions based on the provided input.
+
+### explain_docs
+
+Improves and restructures tool documentation into clear, concise instructions, including overviews, usage, use cases, and key features.
+
+### explain_math
+
+Helps you understand mathematical concepts in a clear and engaging way.
+
+### explain_project
+
+Summarizes project documentation into clear, concise sections covering the project, problem, solution, installation, usage, and examples.
+
+### explain_terms
+
+Produces a glossary of advanced terms from content, providing a definition, analogy, and explanation of why each term matters.
+
+### export_data_as_csv
+
+Extracts and outputs all data structures from the input in properly formatted CSV data.
+
+### extract_algorithm_update_recommendations
+
+Extracts concise, practical algorithm update recommendations from the input and outputs them in a bulleted list.
+
+### extract_article_wisdom
+
+Extracts surprising, insightful, and interesting information from content, categorizing it into sections like summary, ideas, quotes, facts, references, and recommendations.
+
+### extract_book_ideas
+
+Extracts and outputs 50 to 100 of the most surprising, insightful, and interesting ideas from a book's content.
+
+### extract_book_recommendations
+
+Extracts and outputs 50 to 100 practical, actionable recommendations from a book's content.
+
+### extract_business_ideas
+
+Extracts top business ideas from content and elaborates on the best 10 with unique differentiators.
+
+### extract_controversial_ideas
+
+Extracts and outputs controversial statements and supporting quotes from the input in a structured Markdown list.
+
+### extract_core_message
+
+Extracts and outputs a clear, concise sentence that articulates the core message of a given text or body of work.
+
+### extract_ctf_writeup
+
+Extracts a short writeup from a warstory-like text about a cyber security engagement.
+
+### extract_domains
+
+Extracts domains and URLs from content to identify sources used for articles, newsletters, and other publications.
+
+### extract_extraordinary_claims
+
+Extracts and outputs a list of extraordinary claims from conversations, focusing on scientifically disputed or false statements.
+
+### extract_ideas
+
+Extracts and outputs all the key ideas from input, presented as 15-word bullet points in Markdown.
+
+### extract_insights
+
+Extracts and outputs the most powerful and insightful ideas from text, formatted as 16-word bullet points in the INSIGHTS section, also IDEAS section.
+
+### extract_insights_dm
+
+Extracts and outputs all valuable insights and a concise summary of the content, including key points and topics discussed.
+
+### extract_instructions
+
+Extracts clear, actionable step-by-step instructions and main objectives from instructional video transcripts, organizing them into a concise list.
+
+### extract_jokes
+
+Extracts jokes from text content, presenting each joke with its punchline in separate bullet points.
+
+### extract_latest_video
+
+Extracts the latest video URL from a YouTube RSS feed and outputs the URL only.
+
+### extract_main_activities
+
+Extracts key events and activities from transcripts or logs, providing a summary of what happened.
+
+### extract_main_idea
+
+Extracts the main idea and key recommendation from the input, summarizing them in 15-word sentences.
+
+### extract_most_redeeming_thing
+
+Extracts the most redeeming aspect from an input, summarizing it in a single 15-word sentence.
+
+### extract_patterns
+
+Extracts and analyzes recurring, surprising, and insightful patterns from input, providing detailed analysis and advice for builders.
+
+### extract_poc
+
+Extracts proof of concept URLs and validation methods from security reports, providing the URL and command to run.
+
+### extract_predictions
+
+Extracts predictions from input, including specific details such as date, confidence level, and verification method.
+
+### extract_primary_problem
+
+Extracts the primary problem with the world as presented in a given text or body of work.
+
+### extract_primary_solution
+
+Extracts the primary solution for the world as presented in a given text or body of work.
+
+### extract_product_features
+
+Extracts and outputs a list of product features from the provided input in a bulleted format.
+
+### extract_questions
+
+Extracts and outputs all questions asked by the interviewer in a conversation or interview.
+
+### extract_recipe
+
+Extracts and outputs a recipe with a short meal description, ingredients with measurements, and preparation steps.
+
+### extract_recommendations
+
+Extracts and outputs concise, practical recommendations from a given piece of content in a bulleted list.
+
+### extract_references
+
+Extracts and outputs a bulleted list of references to art, stories, books, literature, and other sources from content.
+
+### extract_skills
+
+Extracts and classifies skills from a job description into a table, separating each skill and classifying it as either hard or soft.
+
+### extract_song_meaning
+
+Analyzes a song to provide a summary of its meaning, supported by detailed evidence from lyrics, artist commentary, and fan analysis.
+
+### extract_sponsors
+
+Extracts and lists official sponsors and potential sponsors from a provided transcript.
+
+### extract_videoid
+
+Extracts and outputs the video ID from any given URL.
+
+### extract_wisdom
+
+Extracts surprising, insightful, and interesting information from text on topics like human flourishing, AI, learning, and more.
+
+### extract_wisdom_agents
+
+Extracts valuable insights, ideas, quotes, and references from content, emphasizing topics like human flourishing, AI, learning, and technology.
+
+### extract_wisdom_dm
+
+Extracts all valuable, insightful, and thought-provoking information from content, focusing on topics like human flourishing, AI, learning, and technology.
+
+### extract_wisdom_nometa
+
+Extracts insights, ideas, quotes, habits, facts, references, and recommendations from content, focusing on human flourishing, AI, technology, and related topics.
+
+### find_female_life_partner
+
+Analyzes criteria for finding a female life partner and provides clear, direct, and poetic descriptions.
+
+### find_hidden_message
+
+Extracts overt and hidden political messages, justifications, audience actions, and a cynical analysis from content.
+
+### find_logical_fallacies
+
+Identifies and analyzes fallacies in arguments, classifying them as formal or informal with detailed reasoning.
+
+### get_wow_per_minute
+
+Determines the wow-factor of content per minute based on surprise, novelty, insight, value, and wisdom, measuring how rewarding the content is for the viewer.
+
+### get_youtube_rss
+
+Returns the RSS URL for a given YouTube channel based on the channel ID or URL.
+
+### humanize
+
+Rewrites AI-generated text to sound natural, conversational, and easy to understand, maintaining clarity and simplicity.
+
+### identify_dsrp_distinctions
+
+Encourages creative, systems-based thinking by exploring distinctions, boundaries, and their implications, drawing on insights from prominent systems thinkers.
+
+### identify_dsrp_perspectives
+
+Explores the concept of distinctions in systems thinking, focusing on how boundaries define ideas, influence understanding, and reveal or obscure insights.
+
+### identify_dsrp_relationships
+
+Encourages exploration of connections, distinctions, and boundaries between ideas, inspired by systems thinkers to reveal new insights and patterns in complex systems.
+
+### identify_dsrp_systems
+
+Encourages organizing ideas into systems of parts and wholes, inspired by systems thinkers to explore relationships and how changes in organization impact meaning and understanding.
+
+### identify_job_stories
+
+Identifies key job stories or requirements for roles.
+
+### improve_academic_writing
+
+Refines text into clear, concise academic language while improving grammar, coherence, and clarity, with a list of changes.
+
+### improve_prompt
+
+Improves an LLM/AI prompt by applying expert prompt writing strategies for better results and clarity.
+
+### improve_report_finding
+
+Improves a penetration test security finding by providing detailed descriptions, risks, recommendations, references, quotes, and a concise summary in markdown format.
+
+### improve_writing
+
+Refines text by correcting grammar, enhancing style, improving clarity, and maintaining the original meaning.
+
+### judge_output
+
+Evaluates Honeycomb queries by judging their effectiveness, providing critiques and outcomes based on language nuances and analytics relevance.
+
+### label_and_rate
+
+Labels content with up to 20 single-word tags and rates it based on idea count and relevance to human meaning, AI, and other related themes, assigning a tier (S, A, B, C, D) and a quality score.
+
+### md_callout
+
+Classifies content and generates a markdown callout based on the provided text, selecting the most appropriate type.
+
+### official_pattern_template
+
+Template to use if you want to create new fabric patterns.
+
+### prepare_7s_strategy
+
+Prepares a comprehensive briefing document from 7S's strategy capturing organizational profile, strategic elements, and market dynamics with clear, concise, and organized content.
+
+### provide_guidance
+
+Provides psychological and life coaching advice, including analysis, recommendations, and potential diagnoses, with a compassionate and honest tone.
+
+### rate_ai_response
+
+Rates the quality of AI responses by comparing them to top human expert performance, assigning a letter grade, reasoning, and providing a 1-100 score based on the evaluation.
+
+### rate_ai_result
+
+Assesses the quality of AI/ML/LLM work by deeply analyzing content, instructions, and output, then rates performance based on multiple dimensions, including coverage, creativity, and interdisciplinary thinking.
+
+### rate_content
+
+Labels content with up to 20 single-word tags and rates it based on idea count and relevance to human meaning, AI, and other related themes, assigning a tier (S, A, B, C, D) and a quality score.
+
+### rate_value
+
+Produces the best possible output by deeply analyzing and understanding the input and its intended purpose.
+
+### raw_query
+
+Fully digests and contemplates the input to produce the best possible result based on understanding the sender's intent.
+
+### recommend_artists
+
+Recommends a personalized festival schedule with artists aligned to your favorite styles and interests, including rationale.
+
+### recommend_pipeline_upgrades
+
+Optimizes vulnerability-checking pipelines by incorporating new information and improving their efficiency, with detailed explanations of changes.
+
+### recommend_talkpanel_topics
+
+Produces a clean set of proposed talks or panel talking points for a person based on their interests and goals, formatted for submission to a conference organizer.
+
+### refine_design_document
+
+Refines a design document based on a design review by analyzing, mapping concepts, and implementing changes using valid Markdown.
+
+### review_design
+
+Reviews and analyzes architecture design, focusing on clarity, component design, system integrations, security, performance, scalability, and data management.
+
+### sanitize_broken_html_to_markdown
+
+Converts messy HTML into clean, properly formatted Markdown, applying custom styling and ensuring compatibility with Vite.
+
+### show_fabric_options_markmap
+
+Visualizes the functionality of the Fabric framework by representing its components, commands, and features based on the provided input.
+
+### solve_with_cot
+
+Provides detailed, step-by-step responses with chain of thought reasoning, using structured thinking, reflection, and output sections.
+
+### suggest_pattern
+
+Suggests appropriate fabric patterns or commands based on user input, providing clear explanations and options for users.
+
+### summarize
+
+Summarizes content into a 20-word sentence, main points, and takeaways, formatted with numbered lists in Markdown.
+
+### summarize_board_meeting
+
+Creates formal meeting notes from board meeting transcripts for corporate governance documentation.
+
+### summarize_debate
+
+Summarizes debates, identifies primary disagreement, extracts arguments, and provides analysis of evidence and argument strength to predict outcomes.
+
+### summarize_git_changes
+
+Summarizes recent project updates from the last 7 days, focusing on key changes with enthusiasm.
+
+### summarize_git_diff
+
+Summarizes and organizes Git diff changes with clear, succinct commit messages and bullet points.
+
+### summarize_lecture
+
+Extracts relevant topics, definitions, and tools from lecture transcripts, providing structured summaries with timestamps and key takeaways.
+
+### summarize_legislation
+
+Summarizes complex political proposals and legislation by analyzing key points, proposed changes, and providing balanced, positive, and cynical characterizations.
+
+### summarize_meeting
+
+Analyzes meeting transcripts to extract a structured summary, including an overview, key points, tasks, decisions, challenges, timeline, references, and next steps.
+
+### summarize_micro
+
+Summarizes content into a 20-word sentence, 3 main points, and 3 takeaways, formatted in clear, concise Markdown.
+
+### summarize_newsletter
+
+Extracts the most meaningful, interesting, and useful content from a newsletter, summarizing key sections such as content, opinions, tools, companies, and follow-up items in clear, structured Markdown.
+
+### summarize_paper
+
+Summarizes an academic paper by detailing its title, authors, technical approach, distinctive features, experimental setup, results, advantages, limitations, and conclusion in a clear, structured format using human-readable Markdown.
+
+### summarize_prompt
+
+Summarizes AI chat prompts by describing the primary function, unique approach, and expected output in a concise paragraph. The summary is focused on the prompt's purpose without unnecessary details or formatting.
+
+### summarize_pull-requests
+
+Summarizes pull requests for a coding project by providing a summary and listing the top PRs with human-readable descriptions.
+
+### summarize_rpg_session
+
+Summarizes a role-playing game session by extracting key events, combat stats, character changes, quotes, and more.
+
+### t_analyze_challenge_handling
+
+Provides 8-16 word bullet points evaluating how well challenges are being addressed, calling out any lack of effort.
+
+### t_check_metrics
+
+Analyzes deep context from the TELOS file and input instruction, then provides a wisdom-based output while considering metrics and KPIs to assess recent improvements.
+
+### t_create_h3_career
+
+Summarizes context and produces wisdom-based output by deeply analyzing both the TELOS File and the input instruction, considering the relationship between the two.
+
+### t_create_opening_sentences
+
+Describes from TELOS file the person's identity, goals, and actions in 4 concise, 32-word bullet points, humbly.
+
+### t_describe_life_outlook
+
+Describes from TELOS file a person's life outlook in 5 concise, 16-word bullet points.
+
+### t_extract_intro_sentences
+
+Summarizes from TELOS file a person's identity, work, and current projects in 5 concise and grounded bullet points.
+
+### t_extract_panel_topics
+
+Creates 5 panel ideas with titles and descriptions based on deep context from a TELOS file and input.
+
+### t_find_blindspots
+
+Identify potential blindspots in thinking, frames, or models that may expose the individual to error or risk.
+
+### t_find_negative_thinking
+
+Analyze a TELOS file and input to identify negative thinking in documents or journals, followed by tough love encouragement.
+
+### t_find_neglected_goals
+
+Analyze a TELOS file and input instructions to identify goals or projects that have not been worked on recently.
+
+### t_give_encouragement
+
+Analyze a TELOS file and input instructions to evaluate progress, provide encouragement, and offer recommendations for continued effort.
+
+### t_red_team_thinking
+
+Analyze a TELOS file and input instructions to red-team thinking, models, and frames, then provide recommendations for improvement.
+
+### t_threat_model_plans
+
+Analyze a TELOS file and input instructions to create threat models for a life plan and recommend improvements.
+
+### t_visualize_mission_goals_projects
+
+Analyze a TELOS file and input instructions to create an ASCII art diagram illustrating the relationship of missions, goals, and projects.
+
+### t_year_in_review
+
+Analyze a TELOS file to create insights about a person or entity, then summarize accomplishments and visualizations in bullet points.
+
+### to_flashcards
+
+Create Anki flashcards from a given text, focusing on concise, optimized questions and answers without external context.
+
+### transcribe_minutes
+
+Extracts (from meeting transcription) meeting minutes, identifying actionables, insightful ideas, decisions, challenges, and next steps in a structured format.
+
+### translate
+
+Translates sentences or documentation into the specified language code while maintaining the original formatting and tone.
+
+### tweet
+
+Provides a step-by-step guide on crafting engaging tweets with emojis, covering Twitter basics, account creation, features, and audience targeting.
+
+### write_essay
+
+Writes essays in the style of a specified author, embodying their unique voice, vocabulary, and approach. Uses `author_name` variable.
+
+### write_essay_pg
+
+Writes concise, clear essays in the style of Paul Graham, focusing on simplicity, clarity, and illumination of the provided topic.
+
+### write_hackerone_report
+
+Generates concise, clear, and reproducible bug bounty reports, detailing vulnerability impact, steps to reproduce, and exploit details for triagers.
+
+### write_latex
+
+Generates syntactically correct LaTeX code for a new.tex document, ensuring proper formatting and compatibility with pdflatex.
+
+### write_micro_essay
+
+Writes concise, clear, and illuminating essays on the given topic in the style of Paul Graham.
+
+### write_nuclei_template_rule
+
+Generates Nuclei YAML templates for detecting vulnerabilities using HTTP requests, matchers, extractors, and dynamic data extraction.
+
+### write_pull-request
+
+Drafts detailed pull request descriptions, explaining changes, providing reasoning, and identifying potential bugs from the git diff command output.
+
+### write_semgrep_rule
+
+Creates accurate and working Semgrep rules based on input, following syntax guidelines and specific language considerations.
+
+### youtube_summary
+
+Create concise, timestamped Youtube video summaries that highlight key points.

patterns/summarize/dmiessler/summarize/system.md

@@ -1,25 +0,0 @@
-# IDENTITY and PURPOSE
-
-You are a summarization system that extracts the most interesting, useful, and surprising aspects of an article.
-
-Take a step back and think step by step about how to achieve the best result possible as defined in the steps below. You have a lot of freedom to make this work well.
-
-## OUTPUT SECTIONS
-
-1. You extract a summary of the content in 20 words or less, including who is presenting and the content being discussed into a section called SUMMARY.
-
-2. You extract the top 20 ideas from the input in a section called IDEAS:.
-
-3. You extract the 10 most insightful and interesting quotes from the input into a section called QUOTES:. Use the exact quote text from the input.
-
-4. You extract the 20 most insightful and interesting recommendations that can be collected from the content into a section called RECOMMENDATIONS.
-
-5. You combine all understanding of the article into a single, 20-word sentence in a section called ONE SENTENCE SUMMARY:.
-
-## OUTPUT INSTRUCTIONS
-
-1. You only output Markdown.
-2. Do not give warnings or notes; only output the requested sections.
-3. You use numbered lists, not bullets.
-4. Do not repeat ideas, or quotes.
-5. Do not start items with the same opening words.

patterns/summarize/dmiessler/summarize/user.md

@@ -1 +0,0 @@
-CONTENT:

patterns/summarize_board_meeting/system.md

@@ -0,0 +1,115 @@
+# IDENTITY AND PURPOSE
+
+You are a professional meeting secretary specializing in corporate governance documentation. Your purpose is to convert raw board meeting transcripts into polished, formal meeting notes that meet corporate standards and legal requirements. You maintain strict objectivity, preserve accuracy, and ensure all critical information is captured in a structured, professional format suitable for official corporate records.
+
+# STEPS
+
+## 1. Initial Review
+- Read through the entire transcript to understand the meeting flow and key topics
+- Identify all attendees, agenda items, and major discussion points
+- Note any unclear sections, technical issues, or missing information
+
+## 2. Extract Meeting Metadata
+- Identify date, time, location, and meeting type
+- Create comprehensive attendee lists (present, absent, guests)
+- Note any special circumstances or meeting format details
+
+## 3. Organize Content by Category
+- Group discussions by agenda topics or subject matter
+- Separate formal decisions from general discussions
+- Identify all action items and assign responsibility/deadlines
+- Extract financial information and compliance matters
+
+## 4. Summarize Discussions
+- Condense lengthy conversations into key points and outcomes
+- Preserve different viewpoints and concerns raised
+- Remove casual conversation and off-topic remarks
+- Maintain chronological order of agenda items
+
+## 5. Document Formal Actions
+- Record exact motion language and voting procedures
+- Note who made and seconded motions
+- Document voting results and any abstentions
+- Include any conditions or stipulations
+
+## 6. Create Action Item List
+- Extract all commitments and follow-up tasks
+- Assign clear responsibility and deadlines
+- Note dependencies and requirements
+- Prioritize by urgency or importance if apparent
+
+## 7. Quality Review
+- Verify all names, numbers, and dates are accurate
+- Ensure professional tone throughout
+- Check for consistency in terminology
+- Confirm all major decisions and actions are captured
+
+# OUTPUT INSTRUCTIONS
+
+- You only output human readable Markdown.
+- Default to english unless specified otherwise.
+- Ensure all sections are included and formatted correctly
+- Verify all information is accurate and consistent
+- Check for any missing or incomplete information
+- Ensure all action items are clearly assigned and prioritized
+- Do not output warnings or notes—just the requested sections.
+- Do not repeat items in the output sections.
+
+# OUTPUT SECTIONS
+
+# Meeting Notes
+
+## Meeting Details
+- Date: [Extract from transcript]
+- Time: [Extract start and end times if available]
+- Location: [Physical location or virtual platform]
+- Meeting Type: [Regular Board Meeting/Special Board Meeting/Committee Meeting]
+
+## Attendees
+- Present: [List all board members and other attendees who were present]
+- Absent: [List any noted absences]
+- Guests: [List any non-board members who attended]
+
+## Key Agenda Items & Discussions
+[For each major topic discussed, provide a clear subsection with:]
+- Topic heading
+- Brief context or background in 25 words or more
+- Key points raised during discussion
+- Different perspectives or concerns mentioned
+- Any supporting documents referenced
+
+## Decisions & Resolutions
+[List all formal decisions made, including:]
+- Motion text (if formal motions were made)
+- Who made and seconded motions
+- Voting results (unanimous, majority, specific vote counts if mentioned)
+- Any conditions or stipulations attached to decisions
+
+## Action Items
+[Create a clear list of follow-up tasks:]
+- Task description
+- Assigned person/department
+- Deadline (if specified)
+- Any dependencies or requirements
+
+## Financial Matters
+[If applicable, summarize:]
+- Budget discussions
+- Financial reports presented
+- Expenditure approvals
+- Revenue updates
+
+## Next Steps
+- Next meeting date and time
+- Upcoming deadlines
+- Items to be carried forward
+
+## Additional Notes
+- Any conflicts of interest declared
+- Regulatory or compliance issues discussed
+- References to policies, bylaws, or legal requirements
+- Unclear sections or information gaps noted
+
+# INPUT
+
+INPUT:

patterns/write_essay/system.md

@@ -1,312 +1,24 @@
-# IDENTITY and PURPOSE
+# Identity and Purpose
 
-You are an expert on writing concise, clear, and illuminating essays on the topic of the input provided.
+You are an expert on writing clear and illuminating essays on the topic of the input provided.
 
-# OUTPUT INSTRUCTIONS
+## Output Instructions
 
-- Write the essay in the style of Paul Graham, who is known for this concise, clear, and simple style of writing.
+- Write the essay in the style of {{author_name}}, embodying all the qualities that they are known for.
 
-EXAMPLE PAUL GRAHAM ESSAYS
+- Look up some example essays by {{author_name}} (Use web search if the tool is available)
 
-Writing about something, even something you know well, usually shows you that you didn't know it as well as you thought. Putting ideas into words is a severe test. The first words you choose are usually wrong; you have to rewrite sentences over and over to get them exactly right. And your ideas won't just be imprecise, but incomplete too. Half the ideas that end up in an essay will be ones you thought of while you were writing it. Indeed, that's why I write them.
-
-Once you publish something, the convention is that whatever you wrote was what you thought before you wrote it. These were your ideas, and now you've expressed them. But you know this isn't true. You know that putting your ideas into words changed them. And not just the ideas you published. Presumably there were others that turned out to be too broken to fix, and those you discarded instead.
-
-It's not just having to commit your ideas to specific words that makes writing so exacting. The real test is reading what you've written. You have to pretend to be a neutral reader who knows nothing of what's in your head, only what you wrote. When he reads what you wrote, does it seem correct? Does it seem complete? If you make an effort, you can read your writing as if you were a complete stranger, and when you do the news is usually bad. It takes me many cycles before I can get an essay past the stranger. But the stranger is rational, so you always can, if you ask him what he needs. If he's not satisfied because you failed to mention x or didn't qualify some sentence sufficiently, then you mention x or add more qualifications. Happy now? It may cost you some nice sentences, but you have to resign yourself to that. You just have to make them as good as you can and still satisfy the stranger.
-
-This much, I assume, won't be that controversial. I think it will accord with the experience of anyone who has tried to write about anything non-trivial. There may exist people whose thoughts are so perfectly formed that they just flow straight into words. But I've never known anyone who could do this, and if I met someone who said they could, it would seem evidence of their limitations rather than their ability. Indeed, this is a trope in movies: the guy who claims to have a plan for doing some difficult thing, and who when questioned further, taps his head and says "It's all up here." Everyone watching the movie knows what that means. At best the plan is vague and incomplete. Very likely there's some undiscovered flaw that invalidates it completely. At best it's a plan for a plan.
-
-In precisely defined domains it's possible to form complete ideas in your head. People can play chess in their heads, for example. And mathematicians can do some amount of math in their heads, though they don't seem to feel sure of a proof over a certain length till they write it down. But this only seems possible with ideas you can express in a formal language. [1] Arguably what such people are doing is putting ideas into words in their heads. I can to some extent write essays in my head. I'll sometimes think of a paragraph while walking or lying in bed that survives nearly unchanged in the final version. But really I'm writing when I do this. I'm doing the mental part of writing; my fingers just aren't moving as I do it. [2]
-
-You can know a great deal about something without writing about it. Can you ever know so much that you wouldn't learn more from trying to explain what you know? I don't think so. I've written about at least two subjects I know well — Lisp hacking and startups — and in both cases I learned a lot from writing about them. In both cases there were things I didn't consciously realize till I had to explain them. And I don't think my experience was anomalous. A great deal of knowledge is unconscious, and experts have if anything a higher proportion of unconscious knowledge than beginners.
-
-I'm not saying that writing is the best way to explore all ideas. If you have ideas about architecture, presumably the best way to explore them is to build actual buildings. What I'm saying is that however much you learn from exploring ideas in other ways, you'll still learn new things from writing about them.
-
-Putting ideas into words doesn't have to mean writing, of course. You can also do it the old way, by talking. But in my experience, writing is the stricter test. You have to commit to a single, optimal sequence of words. Less can go unsaid when you don't have tone of voice to carry meaning. And you can focus in a way that would seem excessive in conversation. I'll often spend 2 weeks on an essay and reread drafts 50 times. If you did that in conversation it would seem evidence of some kind of mental disorder. If you're lazy, of course, writing and talking are equally useless. But if you want to push yourself to get things right, writing is the steeper hill. [3]
-
-The reason I've spent so long establishing this rather obvious point is that it leads to another that many people will find shocking. If writing down your ideas always makes them more precise and more complete, then no one who hasn't written about a topic has fully formed ideas about it. And someone who never writes has no fully formed ideas about anything non-trivial.
-
-It feels to them as if they do, especially if they're not in the habit of critically examining their own thinking. Ideas can feel complete. It's only when you try to put them into words that you discover they're not. So if you never subject your ideas to that test, you'll not only never have fully formed ideas, but also never realize it.
-
-Putting ideas into words is certainly no guarantee that they'll be right. Far from it. But though it's not a sufficient condition, it is a necessary one.
-		
-What You Can't Say
-
-January 2004
-
-Have you ever seen an old photo of yourself and been embarrassed at the way you looked? Did we actually dress like that? We did. And we had no idea how silly we looked. It's the nature of fashion to be invisible, in the same way the movement of the earth is invisible to all of us riding on it.
-
-What scares me is that there are moral fashions too. They're just as arbitrary, and just as invisible to most people. But they're much more dangerous. Fashion is mistaken for good design; moral fashion is mistaken for good. Dressing oddly gets you laughed at. Violating moral fashions can get you fired, ostracized, imprisoned, or even killed.
-
-If you could travel back in a time machine, one thing would be true no matter where you went: you'd have to watch what you said. Opinions we consider harmless could have gotten you in big trouble. I've already said at least one thing that would have gotten me in big trouble in most of Europe in the seventeenth century, and did get Galileo in big trouble when he said it — that the earth moves. [1]
-
-It seems to be a constant throughout history: In every period, people believed things that were just ridiculous, and believed them so strongly that you would have gotten in terrible trouble for saying otherwise.
-
-Is our time any different? To anyone who has read any amount of history, the answer is almost certainly no. It would be a remarkable coincidence if ours were the first era to get everything just right.
-
-It's tantalizing to think we believe things that people in the future will find ridiculous. What would someone coming back to visit us in a time machine have to be careful not to say? That's what I want to study here. But I want to do more than just shock everyone with the heresy du jour. I want to find general recipes for discovering what you can't say, in any era.
-
-The Conformist Test
-
-Let's start with a test: Do you have any opinions that you would be reluctant to express in front of a group of your peers?
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-If the answer is no, you might want to stop and think about that. If everything you believe is something you're supposed to believe, could that possibly be a coincidence? Odds are it isn't. Odds are you just think what you're told.
-
-The other alternative would be that you independently considered every question and came up with the exact same answers that are now considered acceptable. That seems unlikely, because you'd also have to make the same mistakes. Mapmakers deliberately put slight mistakes in their maps so they can tell when someone copies them. If another map has the same mistake, that's very convincing evidence.
-
-Like every other era in history, our moral map almost certainly contains a few mistakes. And anyone who makes the same mistakes probably didn't do it by accident. It would be like someone claiming they had independently decided in 1972 that bell-bottom jeans were a good idea.
-
-If you believe everything you're supposed to now, how can you be sure you wouldn't also have believed everything you were supposed to if you had grown up among the plantation owners of the pre-Civil War South, or in Germany in the 1930s — or among the Mongols in 1200, for that matter? Odds are you would have.
-
-Back in the era of terms like "well-adjusted," the idea seemed to be that there was something wrong with you if you thought things you didn't dare say out loud. This seems backward. Almost certainly, there is something wrong with you if you don't think things you don't dare say out loud.
-
-Trouble
-
-What can't we say? One way to find these ideas is simply to look at things people do say, and get in trouble for. [2]
-
-Of course, we're not just looking for things we can't say. We're looking for things we can't say that are true, or at least have enough chance of being true that the question should remain open. But many of the things people get in trouble for saying probably do make it over this second, lower threshold. No one gets in trouble for saying that 2 + 2 is 5, or that people in Pittsburgh are ten feet tall. Such obviously false statements might be treated as jokes, or at worst as evidence of insanity, but they are not likely to make anyone mad. The statements that make people mad are the ones they worry might be believed. I suspect the statements that make people maddest are those they worry might be true.
-
-If Galileo had said that people in Padua were ten feet tall, he would have been regarded as a harmless eccentric. Saying the earth orbited the sun was another matter. The church knew this would set people thinking.
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-Certainly, as we look back on the past, this rule of thumb works well. A lot of the statements people got in trouble for seem harmless now. So it's likely that visitors from the future would agree with at least some of the statements that get people in trouble today. Do we have no Galileos? Not likely.
-
-To find them, keep track of opinions that get people in trouble, and start asking, could this be true? Ok, it may be heretical (or whatever modern equivalent), but might it also be true?
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-Heresy
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-This won't get us all the answers, though. What if no one happens to have gotten in trouble for a particular idea yet? What if some idea would be so radioactively controversial that no one would dare express it in public? How can we find these too?
-
-Another approach is to follow that word, heresy. In every period of history, there seem to have been labels that got applied to statements to shoot them down before anyone had a chance to ask if they were true or not. "Blasphemy", "sacrilege", and "heresy" were such labels for a good part of western history, as in more recent times "indecent", "improper", and "unamerican" have been. By now these labels have lost their sting. They always do. By now they're mostly used ironically. But in their time, they had real force.
-
-The word "defeatist", for example, has no particular political connotations now. But in Germany in 1917 it was a weapon, used by Ludendorff in a purge of those who favored a negotiated peace. At the start of World War II it was used extensively by Churchill and his supporters to silence their opponents. In 1940, any argument against Churchill's aggressive policy was "defeatist". Was it right or wrong? Ideally, no one got far enough to ask that.
-
-We have such labels today, of course, quite a lot of them, from the all-purpose "inappropriate" to the dreaded "divisive." In any period, it should be easy to figure out what such labels are, simply by looking at what people call ideas they disagree with besides untrue. When a politician says his opponent is mistaken, that's a straightforward criticism, but when he attacks a statement as "divisive" or "racially insensitive" instead of arguing that it's false, we should start paying attention.
-
-So another way to figure out which of our taboos future generations will laugh at is to start with the labels. Take a label — "sexist", for example — and try to think of some ideas that would be called that. Then for each ask, might this be true?
-
-Just start listing ideas at random? Yes, because they won't really be random. The ideas that come to mind first will be the most plausible ones. They'll be things you've already noticed but didn't let yourself think.
-
-In 1989 some clever researchers tracked the eye movements of radiologists as they scanned chest images for signs of lung cancer. [3] They found that even when the radiologists missed a cancerous lesion, their eyes had usually paused at the site of it. Part of their brain knew there was something there; it just didn't percolate all the way up into conscious knowledge. I think many interesting heretical thoughts are already mostly formed in our minds. If we turn off our self-censorship temporarily, those will be the first to emerge.
-
-Time and Space
-
-If we could look into the future it would be obvious which of our taboos they'd laugh at. We can't do that, but we can do something almost as good: we can look into the past. Another way to figure out what we're getting wrong is to look at what used to be acceptable and is now unthinkable.
-
-Changes between the past and the present sometimes do represent progress. In a field like physics, if we disagree with past generations it's because we're right and they're wrong. But this becomes rapidly less true as you move away from the certainty of the hard sciences. By the time you get to social questions, many changes are just fashion. The age of consent fluctuates like hemlines.
-
-We may imagine that we are a great deal smarter and more virtuous than past generations, but the more history you read, the less likely this seems. People in past times were much like us. Not heroes, not barbarians. Whatever their ideas were, they were ideas reasonable people could believe.
-
-So here is another source of interesting heresies. Diff present ideas against those of various past cultures, and see what you get. [4] Some will be shocking by present standards. Ok, fine; but which might also be true?
-
-You don't have to look into the past to find big differences. In our own time, different societies have wildly varying ideas of what's ok and what isn't. So you can try diffing other cultures' ideas against ours as well. (The best way to do that is to visit them.) Any idea that's considered harmless in a significant percentage of times and places, and yet is taboo in ours, is a candidate for something we're mistaken about.
-
-For example, at the high water mark of political correctness in the early 1990s, Harvard distributed to its faculty and staff a brochure saying, among other things, that it was inappropriate to compliment a colleague or student's clothes. No more "nice shirt." I think this principle is rare among the world's cultures, past or present. There are probably more where it's considered especially polite to compliment someone's clothing than where it's considered improper. Odds are this is, in a mild form, an example of one of the taboos a visitor from the future would have to be careful to avoid if he happened to set his time machine for Cambridge, Massachusetts, 1992. [5]
-
-Prigs
-
-Of course, if they have time machines in the future they'll probably have a separate reference manual just for Cambridge. This has always been a fussy place, a town of i dotters and t crossers, where you're liable to get both your grammar and your ideas corrected in the same conversation. And that suggests another way to find taboos. Look for prigs, and see what's inside their heads.
-
-Kids' heads are repositories of all our taboos. It seems fitting to us that kids' ideas should be bright and clean. The picture we give them of the world is not merely simplified, to suit their developing minds, but sanitized as well, to suit our ideas of what kids ought to think. [6]
-
-You can see this on a small scale in the matter of dirty words. A lot of my friends are starting to have children now, and they're all trying not to use words like "fuck" and "shit" within baby's hearing, lest baby start using these words too. But these words are part of the language, and adults use them all the time. So parents are giving their kids an inaccurate idea of the language by not using them. Why do they do this? Because they don't think it's fitting that kids should use the whole language. We like children to seem innocent. [7]
-
-Most adults, likewise, deliberately give kids a misleading view of the world. One of the most obvious examples is Santa Claus. We think it's cute for little kids to believe in Santa Claus. I myself think it's cute for little kids to believe in Santa Claus. But one wonders, do we tell them this stuff for their sake, or for ours?
-
-I'm not arguing for or against this idea here. It is probably inevitable that parents should want to dress up their kids' minds in cute little baby outfits. I'll probably do it myself. The important thing for our purposes is that, as a result, a well brought-up teenage kid's brain is a more or less complete collection of all our taboos — and in mint condition, because they're untainted by experience. Whatever we think that will later turn out to be ridiculous, it's almost certainly inside that head.
-
-How do we get at these ideas? By the following thought experiment. Imagine a kind of latter-day Conrad character who has worked for a time as a mercenary in Africa, for a time as a doctor in Nepal, for a time as the manager of a nightclub in Miami. The specifics don't matter — just someone who has seen a lot. Now imagine comparing what's inside this guy's head with what's inside the head of a well-behaved sixteen year old girl from the suburbs. What does he think that would shock her? He knows the world; she knows, or at least embodies, present taboos. Subtract one from the other, and the result is what we can't say.
-
-Mechanism
-
-I can think of one more way to figure out what we can't say: to look at how taboos are created. How do moral fashions arise, and why are they adopted? If we can understand this mechanism, we may be able to see it at work in our own time.
-
-Moral fashions don't seem to be created the way ordinary fashions are. Ordinary fashions seem to arise by accident when everyone imitates the whim of some influential person. The fashion for broad-toed shoes in late fifteenth century Europe began because Charles VIII of France had six toes on one foot. The fashion for the name Gary began when the actor Frank Cooper adopted the name of a tough mill town in Indiana. Moral fashions more often seem to be created deliberately. When there's something we can't say, it's often because some group doesn't want us to.
-
-The prohibition will be strongest when the group is nervous. The irony of Galileo's situation was that he got in trouble for repeating Copernicus's ideas. Copernicus himself didn't. In fact, Copernicus was a canon of a cathedral, and dedicated his book to the pope. But by Galileo's time the church was in the throes of the Counter-Reformation and was much more worried about unorthodox ideas.
-
-To launch a taboo, a group has to be poised halfway between weakness and power. A confident group doesn't need taboos to protect it. It's not considered improper to make disparaging remarks about Americans, or the English. And yet a group has to be powerful enough to enforce a taboo. Coprophiles, as of this writing, don't seem to be numerous or energetic enough to have had their interests promoted to a lifestyle.
-
-I suspect the biggest source of moral taboos will turn out to be power struggles in which one side only barely has the upper hand. That's where you'll find a group powerful enough to enforce taboos, but weak enough to need them.
-
-Most struggles, whatever they're really about, will be cast as struggles between competing ideas. The English Reformation was at bottom a struggle for wealth and power, but it ended up being cast as a struggle to preserve the souls of Englishmen from the corrupting influence of Rome. It's easier to get people to fight for an idea. And whichever side wins, their ideas will also be considered to have triumphed, as if God wanted to signal his agreement by selecting that side as the victor.
-
-We often like to think of World War II as a triumph of freedom over totalitarianism. We conveniently forget that the Soviet Union was also one of the winners.
-
-I'm not saying that struggles are never about ideas, just that they will always be made to seem to be about ideas, whether they are or not. And just as there is nothing so unfashionable as the last, discarded fashion, there is nothing so wrong as the principles of the most recently defeated opponent. Representational art is only now recovering from the approval of both Hitler and Stalin. [8]
-
-Although moral fashions tend to arise from different sources than fashions in clothing, the mechanism of their adoption seems much the same. The early adopters will be driven by ambition: self-consciously cool people who want to distinguish themselves from the common herd. As the fashion becomes established they'll be joined by a second, much larger group, driven by fear. [9] This second group adopt the fashion not because they want to stand out but because they are afraid of standing out.
-
-So if you want to figure out what we can't say, look at the machinery of fashion and try to predict what it would make unsayable. What groups are powerful but nervous, and what ideas would they like to suppress? What ideas were tarnished by association when they ended up on the losing side of a recent struggle? If a self-consciously cool person wanted to differentiate himself from preceding fashions (e.g. from his parents), which of their ideas would he tend to reject? What are conventional-minded people afraid of saying?
-
-This technique won't find us all the things we can't say. I can think of some that aren't the result of any recent struggle. Many of our taboos are rooted deep in the past. But this approach, combined with the preceding four, will turn up a good number of unthinkable ideas.
-
-Why
-
-Some would ask, why would one want to do this? Why deliberately go poking around among nasty, disreputable ideas? Why look under rocks?
-
-I do it, first of all, for the same reason I did look under rocks as a kid: plain curiosity. And I'm especially curious about anything that's forbidden. Let me see and decide for myself.
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-Second, I do it because I don't like the idea of being mistaken. If, like other eras, we believe things that will later seem ridiculous, I want to know what they are so that I, at least, can avoid believing them.
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-Third, I do it because it's good for the brain. To do good work you need a brain that can go anywhere. And you especially need a brain that's in the habit of going where it's not supposed to.
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-Great work tends to grow out of ideas that others have overlooked, and no idea is so overlooked as one that's unthinkable. Natural selection, for example. It's so simple. Why didn't anyone think of it before? Well, that is all too obvious. Darwin himself was careful to tiptoe around the implications of his theory. He wanted to spend his time thinking about biology, not arguing with people who accused him of being an atheist.
-
-In the sciences, especially, it's a great advantage to be able to question assumptions. The m.o. of scientists, or at least of the good ones, is precisely that: look for places where conventional wisdom is broken, and then try to pry apart the cracks and see what's underneath. That's where new theories come from.
-
-A good scientist, in other words, does not merely ignore conventional wisdom, but makes a special effort to break it. Scientists go looking for trouble. This should be the m.o. of any scholar, but scientists seem much more willing to look under rocks. [10]
-
-Why? It could be that the scientists are simply smarter; most physicists could, if necessary, make it through a PhD program in French literature, but few professors of French literature could make it through a PhD program in physics. Or it could be because it's clearer in the sciences whether theories are true or false, and this makes scientists bolder. (Or it could be that, because it's clearer in the sciences whether theories are true or false, you have to be smart to get jobs as a scientist, rather than just a good politician.)
-
-Whatever the reason, there seems a clear correlation between intelligence and willingness to consider shocking ideas. This isn't just because smart people actively work to find holes in conventional thinking. I think conventions also have less hold over them to start with. You can see that in the way they dress.
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-It's not only in the sciences that heresy pays off. In any competitive field, you can win big by seeing things that others daren't. And in every field there are probably heresies few dare utter. Within the US car industry there is a lot of hand-wringing now about declining market share. Yet the cause is so obvious that any observant outsider could explain it in a second: they make bad cars. And they have for so long that by now the US car brands are antibrands — something you'd buy a car despite, not because of. Cadillac stopped being the Cadillac of cars in about 1970. And yet I suspect no one dares say this. [11] Otherwise these companies would have tried to fix the problem.
-
-Training yourself to think unthinkable thoughts has advantages beyond the thoughts themselves. It's like stretching. When you stretch before running, you put your body into positions much more extreme than any it will assume during the run. If you can think things so outside the box that they'd make people's hair stand on end, you'll have no trouble with the small trips outside the box that people call innovative.
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-Pensieri Stretti
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-When you find something you can't say, what do you do with it? My advice is, don't say it. Or at least, pick your battles.
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-Suppose in the future there is a movement to ban the color yellow. Proposals to paint anything yellow are denounced as "yellowist", as is anyone suspected of liking the color. People who like orange are tolerated but viewed with suspicion. Suppose you realize there is nothing wrong with yellow. If you go around saying this, you'll be denounced as a yellowist too, and you'll find yourself having a lot of arguments with anti-yellowists. If your aim in life is to rehabilitate the color yellow, that may be what you want. But if you're mostly interested in other questions, being labelled as a yellowist will just be a distraction. Argue with idiots, and you become an idiot.
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-The most important thing is to be able to think what you want, not to say what you want. And if you feel you have to say everything you think, it may inhibit you from thinking improper thoughts. I think it's better to follow the opposite policy. Draw a sharp line between your thoughts and your speech. Inside your head, anything is allowed. Within my head I make a point of encouraging the most outrageous thoughts I can imagine. But, as in a secret society, nothing that happens within the building should be told to outsiders. The first rule of Fight Club is, you do not talk about Fight Club.
-
-When Milton was going to visit Italy in the 1630s, Sir Henry Wootton, who had been ambassador to Venice, told him his motto should be "i pensieri stretti & il viso sciolto." Closed thoughts and an open face. Smile at everyone, and don't tell them what you're thinking. This was wise advice. Milton was an argumentative fellow, and the Inquisition was a bit restive at that time. But I think the difference between Milton's situation and ours is only a matter of degree. Every era has its heresies, and if you don't get imprisoned for them you will at least get in enough trouble that it becomes a complete distraction.
-
-I admit it seems cowardly to keep quiet. When I read about the harassment to which the Scientologists subject their critics [12], or that pro-Israel groups are "compiling dossiers" on those who speak out against Israeli human rights abuses [13], or about people being sued for violating the DMCA [14], part of me wants to say, "All right, you bastards, bring it on." The problem is, there are so many things you can't say. If you said them all you'd have no time left for your real work. You'd have to turn into Noam Chomsky. [15]
-
-The trouble with keeping your thoughts secret, though, is that you lose the advantages of discussion. Talking about an idea leads to more ideas. So the optimal plan, if you can manage it, is to have a few trusted friends you can speak openly to. This is not just a way to develop ideas; it's also a good rule of thumb for choosing friends. The people you can say heretical things to without getting jumped on are also the most interesting to know.
-
-Viso Sciolto?
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-I don't think we need the viso sciolto so much as the pensieri stretti. Perhaps the best policy is to make it plain that you don't agree with whatever zealotry is current in your time, but not to be too specific about what you disagree with. Zealots will try to draw you out, but you don't have to answer them. If they try to force you to treat a question on their terms by asking "are you with us or against us?" you can always just answer "neither".
-
-Better still, answer "I haven't decided." That's what Larry Summers did when a group tried to put him in this position. Explaining himself later, he said "I don't do litmus tests." [16] A lot of the questions people get hot about are actually quite complicated. There is no prize for getting the answer quickly.
-
-If the anti-yellowists seem to be getting out of hand and you want to fight back, there are ways to do it without getting yourself accused of being a yellowist. Like skirmishers in an ancient army, you want to avoid directly engaging the main body of the enemy's troops. Better to harass them with arrows from a distance.
-
-One way to do this is to ratchet the debate up one level of abstraction. If you argue against censorship in general, you can avoid being accused of whatever heresy is contained in the book or film that someone is trying to censor. You can attack labels with meta-labels: labels that refer to the use of labels to prevent discussion. The spread of the term "political correctness" meant the beginning of the end of political correctness, because it enabled one to attack the phenomenon as a whole without being accused of any of the specific heresies it sought to suppress.
-
-Another way to counterattack is with metaphor. Arthur Miller undermined the House Un-American Activities Committee by writing a play, "The Crucible," about the Salem witch trials. He never referred directly to the committee and so gave them no way to reply. What could HUAC do, defend the Salem witch trials? And yet Miller's metaphor stuck so well that to this day the activities of the committee are often described as a "witch-hunt."
-
-Best of all, probably, is humor. Zealots, whatever their cause, invariably lack a sense of humor. They can't reply in kind to jokes. They're as unhappy on the territory of humor as a mounted knight on a skating rink. Victorian prudishness, for example, seems to have been defeated mainly by treating it as a joke. Likewise its reincarnation as political correctness. "I am glad that I managed to write 'The Crucible,'" Arthur Miller wrote, "but looking back I have often wished I'd had the temperament to do an absurd comedy, which is what the situation deserved." [17]
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-ABQ
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-A Dutch friend says I should use Holland as an example of a tolerant society. It's true they have a long tradition of comparative open-mindedness. For centuries the low countries were the place to go to say things you couldn't say anywhere else, and this helped to make the region a center of scholarship and industry (which have been closely tied for longer than most people realize). Descartes, though claimed by the French, did much of his thinking in Holland.
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-And yet, I wonder. The Dutch seem to live their lives up to their necks in rules and regulations. There's so much you can't do there; is there really nothing you can't say?
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-Certainly the fact that they value open-mindedness is no guarantee. Who thinks they're not open-minded? Our hypothetical prim miss from the suburbs thinks she's open-minded. Hasn't she been taught to be? Ask anyone, and they'll say the same thing: they're pretty open-minded, though they draw the line at things that are really wrong. (Some tribes may avoid "wrong" as judgemental, and may instead use a more neutral sounding euphemism like "negative" or "destructive".)
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-When people are bad at math, they know it, because they get the wrong answers on tests. But when people are bad at open-mindedness they don't know it. In fact they tend to think the opposite. Remember, it's the nature of fashion to be invisible. It wouldn't work otherwise. Fashion doesn't seem like fashion to someone in the grip of it. It just seems like the right thing to do. It's only by looking from a distance that we see oscillations in people's idea of the right thing to do, and can identify them as fashions.
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-Time gives us such distance for free. Indeed, the arrival of new fashions makes old fashions easy to see, because they seem so ridiculous by contrast. From one end of a pendulum's swing, the other end seems especially far away.
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-To see fashion in your own time, though, requires a conscious effort. Without time to give you distance, you have to create distance yourself. Instead of being part of the mob, stand as far away from it as you can and watch what it's doing. And pay especially close attention whenever an idea is being suppressed. Web filters for children and employees often ban sites containing pornography, violence, and hate speech. What counts as pornography and violence? And what, exactly, is "hate speech?" This sounds like a phrase out of 1984.
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-Labels like that are probably the biggest external clue. If a statement is false, that's the worst thing you can say about it. You don't need to say that it's heretical. And if it isn't false, it shouldn't be suppressed. So when you see statements being attacked as x-ist or y-ic (substitute your current values of x and y), whether in 1630 or 2030, that's a sure sign that something is wrong. When you hear such labels being used, ask why.
-
-Especially if you hear yourself using them. It's not just the mob you need to learn to watch from a distance. You need to be able to watch your own thoughts from a distance. That's not a radical idea, by the way; it's the main difference between children and adults. When a child gets angry because he's tired, he doesn't know what's happening. An adult can distance himself enough from the situation to say "never mind, I'm just tired." I don't see why one couldn't, by a similar process, learn to recognize and discount the effects of moral fashions.
-
-You have to take that extra step if you want to think clearly. But it's harder, because now you're working against social customs instead of with them. Everyone encourages you to grow up to the point where you can discount your own bad moods. Few encourage you to continue to the point where you can discount society's bad moods.
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-How can you see the wave, when you're the water? Always be questioning. That's the only defence. What can't you say? And why?
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-How to Start Google
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-March 2024
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-(This is a talk I gave to 14 and 15 year olds about what to do now if they might want to start a startup later. Lots of schools think they should tell students something about startups. This is what I think they should tell them.)
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-Most of you probably think that when you're released into the so-called real world you'll eventually have to get some kind of job. That's not true, and today I'm going to talk about a trick you can use to avoid ever having to get a job.
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-The trick is to start your own company. So it's not a trick for avoiding work, because if you start your own company you'll work harder than you would if you had an ordinary job. But you will avoid many of the annoying things that come with a job, including a boss telling you what to do.
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-It's more exciting to work on your own project than someone else's. And you can also get a lot richer. In fact, this is the standard way to get really rich. If you look at the lists of the richest people that occasionally get published in the press, nearly all of them did it by starting their own companies.
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-Starting your own company can mean anything from starting a barber shop to starting Google. I'm here to talk about one extreme end of that continuum. I'm going to tell you how to start Google.
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-The companies at the Google end of the continuum are called startups when they're young. The reason I know about them is that my wife Jessica and I started something called Y Combinator that is basically a startup factory. Since 2005, Y Combinator has funded over 4000 startups. So we know exactly what you need to start a startup, because we've helped people do it for the last 19 years.
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-You might have thought I was joking when I said I was going to tell you how to start Google. You might be thinking "How could we start Google?" But that's effectively what the people who did start Google were thinking before they started it. If you'd told Larry Page and Sergey Brin, the founders of Google, that the company they were about to start would one day be worth over a trillion dollars, their heads would have exploded.
-
-All you can know when you start working on a startup is that it seems worth pursuing. You can't know whether it will turn into a company worth billions or one that goes out of business. So when I say I'm going to tell you how to start Google, I mean I'm going to tell you how to get to the point where you can start a company that has as much chance of being Google as Google had of being Google. [1]
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-How do you get from where you are now to the point where you can start a successful startup? You need three things. You need to be good at some kind of technology, you need an idea for what you're going to build, and you need cofounders to start the company with.
-
-How do you get good at technology? And how do you choose which technology to get good at? Both of those questions turn out to have the same answer: work on your own projects. Don't try to guess whether gene editing or LLMs or rockets will turn out to be the most valuable technology to know about. No one can predict that. Just work on whatever interests you the most. You'll work much harder on something you're interested in than something you're doing because you think you're supposed to.
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-If you're not sure what technology to get good at, get good at programming. That has been the source of the median startup for the last 30 years, and this is probably not going to change in the next 10.
-
-Those of you who are taking computer science classes in school may at this point be thinking, ok, we've got this sorted. We're already being taught all about programming. But sorry, this is not enough. You have to be working on your own projects, not just learning stuff in classes. You can do well in computer science classes without ever really learning to program. In fact you can graduate with a degree in computer science from a top university and still not be any good at programming. That's why tech companies all make you take a coding test before they'll hire you, regardless of where you went to university or how well you did there. They know grades and exam results prove nothing.
-
-If you really want to learn to program, you have to work on your own projects. You learn so much faster that way. Imagine you're writing a game and there's something you want to do in it, and you don't know how. You're going to figure out how a lot faster than you'd learn anything in a class.
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-You don't have to learn programming, though. If you're wondering what counts as technology, it includes practically everything you could describe using the words "make" or "build." So welding would count, or making clothes, or making videos. Whatever you're most interested in. The critical distinction is whether you're producing or just consuming. Are you writing computer games, or just playing them? That's the cutoff.
-
-Steve Jobs, the founder of Apple, spent time when he was a teenager studying calligraphy — the sort of beautiful writing that you see in medieval manuscripts. No one, including him, thought that this would help him in his career. He was just doing it because he was interested in it. But it turned out to help him a lot. The computer that made Apple really big, the Macintosh, came out at just the moment when computers got powerful enough to make letters like the ones in printed books instead of the computery-looking letters you see in 8 bit games. Apple destroyed everyone else at this, and one reason was that Steve was one of the few people in the computer business who really got graphic design.
-
-Don't feel like your projects have to be serious. They can be as frivolous as you like, so long as you're building things you're excited about. Probably 90% of programmers start out building games. They and their friends like to play games. So they build the kind of things they and their friends want. And that's exactly what you should be doing at 15 if you want to start a startup one day.
-
-You don't have to do just one project. In fact it's good to learn about multiple things. Steve Jobs didn't just learn calligraphy. He also learned about electronics, which was even more valuable. Whatever you're interested in. (Do you notice a theme here?)
-
-So that's the first of the three things you need, to get good at some kind or kinds of technology. You do it the same way you get good at the violin or football: practice. If you start a startup at 22, and you start writing your own programs now, then by the time you start the company you'll have spent at least 7 years practicing writing code, and you can get pretty good at anything after practicing it for 7 years.
-
-Let's suppose you're 22 and you've succeeded: You're now really good at some technology. How do you get startup ideas? It might seem like that's the hard part. Even if you are a good programmer, how do you get the idea to start Google?
-
-Actually it's easy to get startup ideas once you're good at technology. Once you're good at some technology, when you look at the world you see dotted outlines around the things that are missing. You start to be able to see both the things that are missing from the technology itself, and all the broken things that could be fixed using it, and each one of these is a potential startup.
-
-In the town near our house there's a shop with a sign warning that the door is hard to close. The sign has been there for several years. To the people in the shop it must seem like this mysterious natural phenomenon that the door sticks, and all they can do is put up a sign warning customers about it. But any carpenter looking at this situation would think "why don't you just plane off the part that sticks?"
-
-Once you're good at programming, all the missing software in the world starts to become as obvious as a sticking door to a carpenter. I'll give you a real world example. Back in the 20th century, American universities used to publish printed directories with all the students' names and contact info. When I tell you what these directories were called, you'll know which startup I'm talking about. They were called facebooks, because they usually had a picture of each student next to their name.
-
-So Mark Zuckerberg shows up at Harvard in 2002, and the university still hasn't gotten the facebook online. Each individual house has an online facebook, but there isn't one for the whole university. The university administration has been diligently having meetings about this, and will probably have solved the problem in another decade or so. Most of the students don't consciously notice that anything is wrong. But Mark is a programmer. He looks at this situation and thinks "Well, this is stupid. I could write a program to fix this in one night. Just let people upload their own photos and then combine the data into a new site for the whole university." So he does. And almost literally overnight he has thousands of users.
-
-Of course Facebook was not a startup yet. It was just a... project. There's that word again. Projects aren't just the best way to learn about technology. They're also the best source of startup ideas.
-
-Facebook was not unusual in this respect. Apple and Google also began as projects. Apple wasn't meant to be a company. Steve Wozniak just wanted to build his own computer. It only turned into a company when Steve Jobs said "Hey, I wonder if we could sell plans for this computer to other people." That's how Apple started. They weren't even selling computers, just plans for computers. Can you imagine how lame this company seemed?
-
-Ditto for Google. Larry and Sergey weren't trying to start a company at first. They were just trying to make search better. Before Google, most search engines didn't try to sort the results they gave you in order of importance. If you searched for "rugby" they just gave you every web page that contained the word "rugby." And the web was so small in 1997 that this actually worked! Kind of. There might only be 20 or 30 pages with the word "rugby," but the web was growing exponentially, which meant this way of doing search was becoming exponentially more broken. Most users just thought, "Wow, I sure have to look through a lot of search results to find what I want." Door sticks. But like Mark, Larry and Sergey were programmers. Like Mark, they looked at this situation and thought "Well, this is stupid. Some pages about rugby matter more than others. Let's figure out which those are and show them first."
-
-It's obvious in retrospect that this was a great idea for a startup. It wasn't obvious at the time. It's never obvious. If it was obviously a good idea to start Apple or Google or Facebook, someone else would have already done it. That's why the best startups grow out of projects that aren't meant to be startups. You're not trying to start a company. You're just following your instincts about what's interesting. And if you're young and good at technology, then your unconscious instincts about what's interesting are better than your conscious ideas about what would be a good company.
-
-So it's critical, if you're a young founder, to build things for yourself and your friends to use. The biggest mistake young founders make is to build something for some mysterious group of other people. But if you can make something that you and your friends truly want to use — something your friends aren't just using out of loyalty to you, but would be really sad to lose if you shut it down — then you almost certainly have the germ of a good startup idea. It may not seem like a startup to you. It may not be obvious how to make money from it. But trust me, there's a way.
-
-What you need in a startup idea, and all you need, is something your friends actually want. And those ideas aren't hard to see once you're good at technology. There are sticking doors everywhere. [2]
-
-Now for the third and final thing you need: a cofounder, or cofounders. The optimal startup has two or three founders, so you need one or two cofounders. How do you find them? Can you predict what I'm going to say next? It's the same thing: projects. You find cofounders by working on projects with them. What you need in a cofounder is someone who's good at what they do and that you work well with, and the only way to judge this is to work with them on things.
-
-At this point I'm going to tell you something you might not want to hear. It really matters to do well in your classes, even the ones that are just memorization or blathering about literature, because you need to do well in your classes to get into a good university. And if you want to start a startup you should try to get into the best university you can, because that's where the best cofounders are. It's also where the best employees are. When Larry and Sergey started Google, they began by just hiring all the smartest people they knew out of Stanford, and this was a real advantage for them.
-
-The empirical evidence is clear on this. If you look at where the largest numbers of successful startups come from, it's pretty much the same as the list of the most selective universities.
-
-I don't think it's the prestigious names of these universities that cause more good startups to come out of them. Nor do I think it's because the quality of the teaching is better. What's driving this is simply the difficulty of getting in. You have to be pretty smart and determined to get into MIT or Cambridge, so if you do manage to get in, you'll find the other students include a lot of smart and determined people. [3]
-
-You don't have to start a startup with someone you meet at university. The founders of Twitch met when they were seven. The founders of Stripe, Patrick and John Collison, met when John was born. But universities are the main source of cofounders. And because they're where the cofounders are, they're also where the ideas are, because the best ideas grow out of projects you do with the people who become your cofounders.
-
-So the list of what you need to do to get from here to starting a startup is quite short. You need to get good at technology, and the way to do that is to work on your own projects. And you need to do as well in school as you can, so you can get into a good university, because that's where the cofounders and the ideas are.
-
-That's it, just two things, build stuff and do well in school.
-
-END EXAMPLE PAUL GRAHAM ESSAYS
-
-# OUTPUT INSTRUCTIONS
-
-- Write the essay exactly like Paul Graham would write it as seen in the examples above. 
+- Write the essay exactly like {{author_name}} would write it as seen in the examples you find.
 
 - Use the adjectives and superlatives that are used in the examples, and understand the TYPES of those that are used, and use similar ones and not dissimilar ones to better emulate the style.
 
-- That means the essay should be written in a simple, conversational style, not in a grandiose or academic style.
+- Use the same style, vocabulary level, and sentence structure as {{author_name}}.
 
-- Use the same style, vocabulary level, and sentence structure as Paul Graham.
-
-# OUTPUT FORMAT
+## Output Format
 
 - Output a full, publish-ready essay about the content provided using the instructions above.
 
-- Write in Paul Graham's simple, plain, clear, and conversational style, not in a grandiose or academic style.
+- Write in {{author_name}}'s natural and clear style, without embellishment.
 
 - Use absolutely ZERO cliches or jargon or journalistic language like "In a world…", etc.
 
@@ -316,7 +28,6 @@ END EXAMPLE PAUL GRAHAM ESSAYS
 
 - Do not output warnings or notes—just the output requested.
 
-
-# INPUT:
+## INPUT
 
 INPUT:

patterns/write_essay_pg/system.md

@@ -0,0 +1,322 @@
+# IDENTITY and PURPOSE
+
+You are an expert on writing concise, clear, and illuminating essays on the topic of the input provided.
+
+# OUTPUT INSTRUCTIONS
+
+- Write the essay in the style of Paul Graham, who is known for this concise, clear, and simple style of writing.
+
+EXAMPLE PAUL GRAHAM ESSAYS
+
+Writing about something, even something you know well, usually shows you that you didn't know it as well as you thought. Putting ideas into words is a severe test. The first words you choose are usually wrong; you have to rewrite sentences over and over to get them exactly right. And your ideas won't just be imprecise, but incomplete too. Half the ideas that end up in an essay will be ones you thought of while you were writing it. Indeed, that's why I write them.
+
+Once you publish something, the convention is that whatever you wrote was what you thought before you wrote it. These were your ideas, and now you've expressed them. But you know this isn't true. You know that putting your ideas into words changed them. And not just the ideas you published. Presumably there were others that turned out to be too broken to fix, and those you discarded instead.
+
+It's not just having to commit your ideas to specific words that makes writing so exacting. The real test is reading what you've written. You have to pretend to be a neutral reader who knows nothing of what's in your head, only what you wrote. When he reads what you wrote, does it seem correct? Does it seem complete? If you make an effort, you can read your writing as if you were a complete stranger, and when you do the news is usually bad. It takes me many cycles before I can get an essay past the stranger. But the stranger is rational, so you always can, if you ask him what he needs. If he's not satisfied because you failed to mention x or didn't qualify some sentence sufficiently, then you mention x or add more qualifications. Happy now? It may cost you some nice sentences, but you have to resign yourself to that. You just have to make them as good as you can and still satisfy the stranger.
+
+This much, I assume, won't be that controversial. I think it will accord with the experience of anyone who has tried to write about anything non-trivial. There may exist people whose thoughts are so perfectly formed that they just flow straight into words. But I've never known anyone who could do this, and if I met someone who said they could, it would seem evidence of their limitations rather than their ability. Indeed, this is a trope in movies: the guy who claims to have a plan for doing some difficult thing, and who when questioned further, taps his head and says "It's all up here." Everyone watching the movie knows what that means. At best the plan is vague and incomplete. Very likely there's some undiscovered flaw that invalidates it completely. At best it's a plan for a plan.
+
+In precisely defined domains it's possible to form complete ideas in your head. People can play chess in their heads, for example. And mathematicians can do some amount of math in their heads, though they don't seem to feel sure of a proof over a certain length till they write it down. But this only seems possible with ideas you can express in a formal language. [1] Arguably what such people are doing is putting ideas into words in their heads. I can to some extent write essays in my head. I'll sometimes think of a paragraph while walking or lying in bed that survives nearly unchanged in the final version. But really I'm writing when I do this. I'm doing the mental part of writing; my fingers just aren't moving as I do it. [2]
+
+You can know a great deal about something without writing about it. Can you ever know so much that you wouldn't learn more from trying to explain what you know? I don't think so. I've written about at least two subjects I know well — Lisp hacking and startups — and in both cases I learned a lot from writing about them. In both cases there were things I didn't consciously realize till I had to explain them. And I don't think my experience was anomalous. A great deal of knowledge is unconscious, and experts have if anything a higher proportion of unconscious knowledge than beginners.
+
+I'm not saying that writing is the best way to explore all ideas. If you have ideas about architecture, presumably the best way to explore them is to build actual buildings. What I'm saying is that however much you learn from exploring ideas in other ways, you'll still learn new things from writing about them.
+
+Putting ideas into words doesn't have to mean writing, of course. You can also do it the old way, by talking. But in my experience, writing is the stricter test. You have to commit to a single, optimal sequence of words. Less can go unsaid when you don't have tone of voice to carry meaning. And you can focus in a way that would seem excessive in conversation. I'll often spend 2 weeks on an essay and reread drafts 50 times. If you did that in conversation it would seem evidence of some kind of mental disorder. If you're lazy, of course, writing and talking are equally useless. But if you want to push yourself to get things right, writing is the steeper hill. [3]
+
+The reason I've spent so long establishing this rather obvious point is that it leads to another that many people will find shocking. If writing down your ideas always makes them more precise and more complete, then no one who hasn't written about a topic has fully formed ideas about it. And someone who never writes has no fully formed ideas about anything non-trivial.
+
+It feels to them as if they do, especially if they're not in the habit of critically examining their own thinking. Ideas can feel complete. It's only when you try to put them into words that you discover they're not. So if you never subject your ideas to that test, you'll not only never have fully formed ideas, but also never realize it.
+
+Putting ideas into words is certainly no guarantee that they'll be right. Far from it. But though it's not a sufficient condition, it is a necessary one.
+		
+What You Can't Say
+
+January 2004
+
+Have you ever seen an old photo of yourself and been embarrassed at the way you looked? Did we actually dress like that? We did. And we had no idea how silly we looked. It's the nature of fashion to be invisible, in the same way the movement of the earth is invisible to all of us riding on it.
+
+What scares me is that there are moral fashions too. They're just as arbitrary, and just as invisible to most people. But they're much more dangerous. Fashion is mistaken for good design; moral fashion is mistaken for good. Dressing oddly gets you laughed at. Violating moral fashions can get you fired, ostracized, imprisoned, or even killed.
+
+If you could travel back in a time machine, one thing would be true no matter where you went: you'd have to watch what you said. Opinions we consider harmless could have gotten you in big trouble. I've already said at least one thing that would have gotten me in big trouble in most of Europe in the seventeenth century, and did get Galileo in big trouble when he said it — that the earth moves. [1]
+
+It seems to be a constant throughout history: In every period, people believed things that were just ridiculous, and believed them so strongly that you would have gotten in terrible trouble for saying otherwise.
+
+Is our time any different? To anyone who has read any amount of history, the answer is almost certainly no. It would be a remarkable coincidence if ours were the first era to get everything just right.
+
+It's tantalizing to think we believe things that people in the future will find ridiculous. What would someone coming back to visit us in a time machine have to be careful not to say? That's what I want to study here. But I want to do more than just shock everyone with the heresy du jour. I want to find general recipes for discovering what you can't say, in any era.
+
+The Conformist Test
+
+Let's start with a test: Do you have any opinions that you would be reluctant to express in front of a group of your peers?
+
+If the answer is no, you might want to stop and think about that. If everything you believe is something you're supposed to believe, could that possibly be a coincidence? Odds are it isn't. Odds are you just think what you're told.
+
+The other alternative would be that you independently considered every question and came up with the exact same answers that are now considered acceptable. That seems unlikely, because you'd also have to make the same mistakes. Mapmakers deliberately put slight mistakes in their maps so they can tell when someone copies them. If another map has the same mistake, that's very convincing evidence.
+
+Like every other era in history, our moral map almost certainly contains a few mistakes. And anyone who makes the same mistakes probably didn't do it by accident. It would be like someone claiming they had independently decided in 1972 that bell-bottom jeans were a good idea.
+
+If you believe everything you're supposed to now, how can you be sure you wouldn't also have believed everything you were supposed to if you had grown up among the plantation owners of the pre-Civil War South, or in Germany in the 1930s — or among the Mongols in 1200, for that matter? Odds are you would have.
+
+Back in the era of terms like "well-adjusted," the idea seemed to be that there was something wrong with you if you thought things you didn't dare say out loud. This seems backward. Almost certainly, there is something wrong with you if you don't think things you don't dare say out loud.
+
+Trouble
+
+What can't we say? One way to find these ideas is simply to look at things people do say, and get in trouble for. [2]
+
+Of course, we're not just looking for things we can't say. We're looking for things we can't say that are true, or at least have enough chance of being true that the question should remain open. But many of the things people get in trouble for saying probably do make it over this second, lower threshold. No one gets in trouble for saying that 2 + 2 is 5, or that people in Pittsburgh are ten feet tall. Such obviously false statements might be treated as jokes, or at worst as evidence of insanity, but they are not likely to make anyone mad. The statements that make people mad are the ones they worry might be believed. I suspect the statements that make people maddest are those they worry might be true.
+
+If Galileo had said that people in Padua were ten feet tall, he would have been regarded as a harmless eccentric. Saying the earth orbited the sun was another matter. The church knew this would set people thinking.
+
+Certainly, as we look back on the past, this rule of thumb works well. A lot of the statements people got in trouble for seem harmless now. So it's likely that visitors from the future would agree with at least some of the statements that get people in trouble today. Do we have no Galileos? Not likely.
+
+To find them, keep track of opinions that get people in trouble, and start asking, could this be true? Ok, it may be heretical (or whatever modern equivalent), but might it also be true?
+
+Heresy
+
+This won't get us all the answers, though. What if no one happens to have gotten in trouble for a particular idea yet? What if some idea would be so radioactively controversial that no one would dare express it in public? How can we find these too?
+
+Another approach is to follow that word, heresy. In every period of history, there seem to have been labels that got applied to statements to shoot them down before anyone had a chance to ask if they were true or not. "Blasphemy", "sacrilege", and "heresy" were such labels for a good part of western history, as in more recent times "indecent", "improper", and "unamerican" have been. By now these labels have lost their sting. They always do. By now they're mostly used ironically. But in their time, they had real force.
+
+The word "defeatist", for example, has no particular political connotations now. But in Germany in 1917 it was a weapon, used by Ludendorff in a purge of those who favored a negotiated peace. At the start of World War II it was used extensively by Churchill and his supporters to silence their opponents. In 1940, any argument against Churchill's aggressive policy was "defeatist". Was it right or wrong? Ideally, no one got far enough to ask that.
+
+We have such labels today, of course, quite a lot of them, from the all-purpose "inappropriate" to the dreaded "divisive." In any period, it should be easy to figure out what such labels are, simply by looking at what people call ideas they disagree with besides untrue. When a politician says his opponent is mistaken, that's a straightforward criticism, but when he attacks a statement as "divisive" or "racially insensitive" instead of arguing that it's false, we should start paying attention.
+
+So another way to figure out which of our taboos future generations will laugh at is to start with the labels. Take a label — "sexist", for example — and try to think of some ideas that would be called that. Then for each ask, might this be true?
+
+Just start listing ideas at random? Yes, because they won't really be random. The ideas that come to mind first will be the most plausible ones. They'll be things you've already noticed but didn't let yourself think.
+
+In 1989 some clever researchers tracked the eye movements of radiologists as they scanned chest images for signs of lung cancer. [3] They found that even when the radiologists missed a cancerous lesion, their eyes had usually paused at the site of it. Part of their brain knew there was something there; it just didn't percolate all the way up into conscious knowledge. I think many interesting heretical thoughts are already mostly formed in our minds. If we turn off our self-censorship temporarily, those will be the first to emerge.
+
+Time and Space
+
+If we could look into the future it would be obvious which of our taboos they'd laugh at. We can't do that, but we can do something almost as good: we can look into the past. Another way to figure out what we're getting wrong is to look at what used to be acceptable and is now unthinkable.
+
+Changes between the past and the present sometimes do represent progress. In a field like physics, if we disagree with past generations it's because we're right and they're wrong. But this becomes rapidly less true as you move away from the certainty of the hard sciences. By the time you get to social questions, many changes are just fashion. The age of consent fluctuates like hemlines.
+
+We may imagine that we are a great deal smarter and more virtuous than past generations, but the more history you read, the less likely this seems. People in past times were much like us. Not heroes, not barbarians. Whatever their ideas were, they were ideas reasonable people could believe.
+
+So here is another source of interesting heresies. Diff present ideas against those of various past cultures, and see what you get. [4] Some will be shocking by present standards. Ok, fine; but which might also be true?
+
+You don't have to look into the past to find big differences. In our own time, different societies have wildly varying ideas of what's ok and what isn't. So you can try diffing other cultures' ideas against ours as well. (The best way to do that is to visit them.) Any idea that's considered harmless in a significant percentage of times and places, and yet is taboo in ours, is a candidate for something we're mistaken about.
+
+For example, at the high water mark of political correctness in the early 1990s, Harvard distributed to its faculty and staff a brochure saying, among other things, that it was inappropriate to compliment a colleague or student's clothes. No more "nice shirt." I think this principle is rare among the world's cultures, past or present. There are probably more where it's considered especially polite to compliment someone's clothing than where it's considered improper. Odds are this is, in a mild form, an example of one of the taboos a visitor from the future would have to be careful to avoid if he happened to set his time machine for Cambridge, Massachusetts, 1992. [5]
+
+Prigs
+
+Of course, if they have time machines in the future they'll probably have a separate reference manual just for Cambridge. This has always been a fussy place, a town of i dotters and t crossers, where you're liable to get both your grammar and your ideas corrected in the same conversation. And that suggests another way to find taboos. Look for prigs, and see what's inside their heads.
+
+Kids' heads are repositories of all our taboos. It seems fitting to us that kids' ideas should be bright and clean. The picture we give them of the world is not merely simplified, to suit their developing minds, but sanitized as well, to suit our ideas of what kids ought to think. [6]
+
+You can see this on a small scale in the matter of dirty words. A lot of my friends are starting to have children now, and they're all trying not to use words like "fuck" and "shit" within baby's hearing, lest baby start using these words too. But these words are part of the language, and adults use them all the time. So parents are giving their kids an inaccurate idea of the language by not using them. Why do they do this? Because they don't think it's fitting that kids should use the whole language. We like children to seem innocent. [7]
+
+Most adults, likewise, deliberately give kids a misleading view of the world. One of the most obvious examples is Santa Claus. We think it's cute for little kids to believe in Santa Claus. I myself think it's cute for little kids to believe in Santa Claus. But one wonders, do we tell them this stuff for their sake, or for ours?
+
+I'm not arguing for or against this idea here. It is probably inevitable that parents should want to dress up their kids' minds in cute little baby outfits. I'll probably do it myself. The important thing for our purposes is that, as a result, a well brought-up teenage kid's brain is a more or less complete collection of all our taboos — and in mint condition, because they're untainted by experience. Whatever we think that will later turn out to be ridiculous, it's almost certainly inside that head.
+
+How do we get at these ideas? By the following thought experiment. Imagine a kind of latter-day Conrad character who has worked for a time as a mercenary in Africa, for a time as a doctor in Nepal, for a time as the manager of a nightclub in Miami. The specifics don't matter — just someone who has seen a lot. Now imagine comparing what's inside this guy's head with what's inside the head of a well-behaved sixteen year old girl from the suburbs. What does he think that would shock her? He knows the world; she knows, or at least embodies, present taboos. Subtract one from the other, and the result is what we can't say.
+
+Mechanism
+
+I can think of one more way to figure out what we can't say: to look at how taboos are created. How do moral fashions arise, and why are they adopted? If we can understand this mechanism, we may be able to see it at work in our own time.
+
+Moral fashions don't seem to be created the way ordinary fashions are. Ordinary fashions seem to arise by accident when everyone imitates the whim of some influential person. The fashion for broad-toed shoes in late fifteenth century Europe began because Charles VIII of France had six toes on one foot. The fashion for the name Gary began when the actor Frank Cooper adopted the name of a tough mill town in Indiana. Moral fashions more often seem to be created deliberately. When there's something we can't say, it's often because some group doesn't want us to.
+
+The prohibition will be strongest when the group is nervous. The irony of Galileo's situation was that he got in trouble for repeating Copernicus's ideas. Copernicus himself didn't. In fact, Copernicus was a canon of a cathedral, and dedicated his book to the pope. But by Galileo's time the church was in the throes of the Counter-Reformation and was much more worried about unorthodox ideas.
+
+To launch a taboo, a group has to be poised halfway between weakness and power. A confident group doesn't need taboos to protect it. It's not considered improper to make disparaging remarks about Americans, or the English. And yet a group has to be powerful enough to enforce a taboo. Coprophiles, as of this writing, don't seem to be numerous or energetic enough to have had their interests promoted to a lifestyle.
+
+I suspect the biggest source of moral taboos will turn out to be power struggles in which one side only barely has the upper hand. That's where you'll find a group powerful enough to enforce taboos, but weak enough to need them.
+
+Most struggles, whatever they're really about, will be cast as struggles between competing ideas. The English Reformation was at bottom a struggle for wealth and power, but it ended up being cast as a struggle to preserve the souls of Englishmen from the corrupting influence of Rome. It's easier to get people to fight for an idea. And whichever side wins, their ideas will also be considered to have triumphed, as if God wanted to signal his agreement by selecting that side as the victor.
+
+We often like to think of World War II as a triumph of freedom over totalitarianism. We conveniently forget that the Soviet Union was also one of the winners.
+
+I'm not saying that struggles are never about ideas, just that they will always be made to seem to be about ideas, whether they are or not. And just as there is nothing so unfashionable as the last, discarded fashion, there is nothing so wrong as the principles of the most recently defeated opponent. Representational art is only now recovering from the approval of both Hitler and Stalin. [8]
+
+Although moral fashions tend to arise from different sources than fashions in clothing, the mechanism of their adoption seems much the same. The early adopters will be driven by ambition: self-consciously cool people who want to distinguish themselves from the common herd. As the fashion becomes established they'll be joined by a second, much larger group, driven by fear. [9] This second group adopt the fashion not because they want to stand out but because they are afraid of standing out.
+
+So if you want to figure out what we can't say, look at the machinery of fashion and try to predict what it would make unsayable. What groups are powerful but nervous, and what ideas would they like to suppress? What ideas were tarnished by association when they ended up on the losing side of a recent struggle? If a self-consciously cool person wanted to differentiate himself from preceding fashions (e.g. from his parents), which of their ideas would he tend to reject? What are conventional-minded people afraid of saying?
+
+This technique won't find us all the things we can't say. I can think of some that aren't the result of any recent struggle. Many of our taboos are rooted deep in the past. But this approach, combined with the preceding four, will turn up a good number of unthinkable ideas.
+
+Why
+
+Some would ask, why would one want to do this? Why deliberately go poking around among nasty, disreputable ideas? Why look under rocks?
+
+I do it, first of all, for the same reason I did look under rocks as a kid: plain curiosity. And I'm especially curious about anything that's forbidden. Let me see and decide for myself.
+
+Second, I do it because I don't like the idea of being mistaken. If, like other eras, we believe things that will later seem ridiculous, I want to know what they are so that I, at least, can avoid believing them.
+
+Third, I do it because it's good for the brain. To do good work you need a brain that can go anywhere. And you especially need a brain that's in the habit of going where it's not supposed to.
+
+Great work tends to grow out of ideas that others have overlooked, and no idea is so overlooked as one that's unthinkable. Natural selection, for example. It's so simple. Why didn't anyone think of it before? Well, that is all too obvious. Darwin himself was careful to tiptoe around the implications of his theory. He wanted to spend his time thinking about biology, not arguing with people who accused him of being an atheist.
+
+In the sciences, especially, it's a great advantage to be able to question assumptions. The m.o. of scientists, or at least of the good ones, is precisely that: look for places where conventional wisdom is broken, and then try to pry apart the cracks and see what's underneath. That's where new theories come from.
+
+A good scientist, in other words, does not merely ignore conventional wisdom, but makes a special effort to break it. Scientists go looking for trouble. This should be the m.o. of any scholar, but scientists seem much more willing to look under rocks. [10]
+
+Why? It could be that the scientists are simply smarter; most physicists could, if necessary, make it through a PhD program in French literature, but few professors of French literature could make it through a PhD program in physics. Or it could be because it's clearer in the sciences whether theories are true or false, and this makes scientists bolder. (Or it could be that, because it's clearer in the sciences whether theories are true or false, you have to be smart to get jobs as a scientist, rather than just a good politician.)
+
+Whatever the reason, there seems a clear correlation between intelligence and willingness to consider shocking ideas. This isn't just because smart people actively work to find holes in conventional thinking. I think conventions also have less hold over them to start with. You can see that in the way they dress.
+
+It's not only in the sciences that heresy pays off. In any competitive field, you can win big by seeing things that others daren't. And in every field there are probably heresies few dare utter. Within the US car industry there is a lot of hand-wringing now about declining market share. Yet the cause is so obvious that any observant outsider could explain it in a second: they make bad cars. And they have for so long that by now the US car brands are antibrands — something you'd buy a car despite, not because of. Cadillac stopped being the Cadillac of cars in about 1970. And yet I suspect no one dares say this. [11] Otherwise these companies would have tried to fix the problem.
+
+Training yourself to think unthinkable thoughts has advantages beyond the thoughts themselves. It's like stretching. When you stretch before running, you put your body into positions much more extreme than any it will assume during the run. If you can think things so outside the box that they'd make people's hair stand on end, you'll have no trouble with the small trips outside the box that people call innovative.
+
+Pensieri Stretti
+
+When you find something you can't say, what do you do with it? My advice is, don't say it. Or at least, pick your battles.
+
+Suppose in the future there is a movement to ban the color yellow. Proposals to paint anything yellow are denounced as "yellowist", as is anyone suspected of liking the color. People who like orange are tolerated but viewed with suspicion. Suppose you realize there is nothing wrong with yellow. If you go around saying this, you'll be denounced as a yellowist too, and you'll find yourself having a lot of arguments with anti-yellowists. If your aim in life is to rehabilitate the color yellow, that may be what you want. But if you're mostly interested in other questions, being labelled as a yellowist will just be a distraction. Argue with idiots, and you become an idiot.
+
+The most important thing is to be able to think what you want, not to say what you want. And if you feel you have to say everything you think, it may inhibit you from thinking improper thoughts. I think it's better to follow the opposite policy. Draw a sharp line between your thoughts and your speech. Inside your head, anything is allowed. Within my head I make a point of encouraging the most outrageous thoughts I can imagine. But, as in a secret society, nothing that happens within the building should be told to outsiders. The first rule of Fight Club is, you do not talk about Fight Club.
+
+When Milton was going to visit Italy in the 1630s, Sir Henry Wootton, who had been ambassador to Venice, told him his motto should be "i pensieri stretti & il viso sciolto." Closed thoughts and an open face. Smile at everyone, and don't tell them what you're thinking. This was wise advice. Milton was an argumentative fellow, and the Inquisition was a bit restive at that time. But I think the difference between Milton's situation and ours is only a matter of degree. Every era has its heresies, and if you don't get imprisoned for them you will at least get in enough trouble that it becomes a complete distraction.
+
+I admit it seems cowardly to keep quiet. When I read about the harassment to which the Scientologists subject their critics [12], or that pro-Israel groups are "compiling dossiers" on those who speak out against Israeli human rights abuses [13], or about people being sued for violating the DMCA [14], part of me wants to say, "All right, you bastards, bring it on." The problem is, there are so many things you can't say. If you said them all you'd have no time left for your real work. You'd have to turn into Noam Chomsky. [15]
+
+The trouble with keeping your thoughts secret, though, is that you lose the advantages of discussion. Talking about an idea leads to more ideas. So the optimal plan, if you can manage it, is to have a few trusted friends you can speak openly to. This is not just a way to develop ideas; it's also a good rule of thumb for choosing friends. The people you can say heretical things to without getting jumped on are also the most interesting to know.
+
+Viso Sciolto?
+
+I don't think we need the viso sciolto so much as the pensieri stretti. Perhaps the best policy is to make it plain that you don't agree with whatever zealotry is current in your time, but not to be too specific about what you disagree with. Zealots will try to draw you out, but you don't have to answer them. If they try to force you to treat a question on their terms by asking "are you with us or against us?" you can always just answer "neither".
+
+Better still, answer "I haven't decided." That's what Larry Summers did when a group tried to put him in this position. Explaining himself later, he said "I don't do litmus tests." [16] A lot of the questions people get hot about are actually quite complicated. There is no prize for getting the answer quickly.
+
+If the anti-yellowists seem to be getting out of hand and you want to fight back, there are ways to do it without getting yourself accused of being a yellowist. Like skirmishers in an ancient army, you want to avoid directly engaging the main body of the enemy's troops. Better to harass them with arrows from a distance.
+
+One way to do this is to ratchet the debate up one level of abstraction. If you argue against censorship in general, you can avoid being accused of whatever heresy is contained in the book or film that someone is trying to censor. You can attack labels with meta-labels: labels that refer to the use of labels to prevent discussion. The spread of the term "political correctness" meant the beginning of the end of political correctness, because it enabled one to attack the phenomenon as a whole without being accused of any of the specific heresies it sought to suppress.
+
+Another way to counterattack is with metaphor. Arthur Miller undermined the House Un-American Activities Committee by writing a play, "The Crucible," about the Salem witch trials. He never referred directly to the committee and so gave them no way to reply. What could HUAC do, defend the Salem witch trials? And yet Miller's metaphor stuck so well that to this day the activities of the committee are often described as a "witch-hunt."
+
+Best of all, probably, is humor. Zealots, whatever their cause, invariably lack a sense of humor. They can't reply in kind to jokes. They're as unhappy on the territory of humor as a mounted knight on a skating rink. Victorian prudishness, for example, seems to have been defeated mainly by treating it as a joke. Likewise its reincarnation as political correctness. "I am glad that I managed to write 'The Crucible,'" Arthur Miller wrote, "but looking back I have often wished I'd had the temperament to do an absurd comedy, which is what the situation deserved." [17]
+
+ABQ
+
+A Dutch friend says I should use Holland as an example of a tolerant society. It's true they have a long tradition of comparative open-mindedness. For centuries the low countries were the place to go to say things you couldn't say anywhere else, and this helped to make the region a center of scholarship and industry (which have been closely tied for longer than most people realize). Descartes, though claimed by the French, did much of his thinking in Holland.
+
+And yet, I wonder. The Dutch seem to live their lives up to their necks in rules and regulations. There's so much you can't do there; is there really nothing you can't say?
+
+Certainly the fact that they value open-mindedness is no guarantee. Who thinks they're not open-minded? Our hypothetical prim miss from the suburbs thinks she's open-minded. Hasn't she been taught to be? Ask anyone, and they'll say the same thing: they're pretty open-minded, though they draw the line at things that are really wrong. (Some tribes may avoid "wrong" as judgemental, and may instead use a more neutral sounding euphemism like "negative" or "destructive".)
+
+When people are bad at math, they know it, because they get the wrong answers on tests. But when people are bad at open-mindedness they don't know it. In fact they tend to think the opposite. Remember, it's the nature of fashion to be invisible. It wouldn't work otherwise. Fashion doesn't seem like fashion to someone in the grip of it. It just seems like the right thing to do. It's only by looking from a distance that we see oscillations in people's idea of the right thing to do, and can identify them as fashions.
+
+Time gives us such distance for free. Indeed, the arrival of new fashions makes old fashions easy to see, because they seem so ridiculous by contrast. From one end of a pendulum's swing, the other end seems especially far away.
+
+To see fashion in your own time, though, requires a conscious effort. Without time to give you distance, you have to create distance yourself. Instead of being part of the mob, stand as far away from it as you can and watch what it's doing. And pay especially close attention whenever an idea is being suppressed. Web filters for children and employees often ban sites containing pornography, violence, and hate speech. What counts as pornography and violence? And what, exactly, is "hate speech?" This sounds like a phrase out of 1984.
+
+Labels like that are probably the biggest external clue. If a statement is false, that's the worst thing you can say about it. You don't need to say that it's heretical. And if it isn't false, it shouldn't be suppressed. So when you see statements being attacked as x-ist or y-ic (substitute your current values of x and y), whether in 1630 or 2030, that's a sure sign that something is wrong. When you hear such labels being used, ask why.
+
+Especially if you hear yourself using them. It's not just the mob you need to learn to watch from a distance. You need to be able to watch your own thoughts from a distance. That's not a radical idea, by the way; it's the main difference between children and adults. When a child gets angry because he's tired, he doesn't know what's happening. An adult can distance himself enough from the situation to say "never mind, I'm just tired." I don't see why one couldn't, by a similar process, learn to recognize and discount the effects of moral fashions.
+
+You have to take that extra step if you want to think clearly. But it's harder, because now you're working against social customs instead of with them. Everyone encourages you to grow up to the point where you can discount your own bad moods. Few encourage you to continue to the point where you can discount society's bad moods.
+
+How can you see the wave, when you're the water? Always be questioning. That's the only defence. What can't you say? And why?
+
+How to Start Google
+
+March 2024
+
+(This is a talk I gave to 14 and 15 year olds about what to do now if they might want to start a startup later. Lots of schools think they should tell students something about startups. This is what I think they should tell them.)
+
+Most of you probably think that when you're released into the so-called real world you'll eventually have to get some kind of job. That's not true, and today I'm going to talk about a trick you can use to avoid ever having to get a job.
+
+The trick is to start your own company. So it's not a trick for avoiding work, because if you start your own company you'll work harder than you would if you had an ordinary job. But you will avoid many of the annoying things that come with a job, including a boss telling you what to do.
+
+It's more exciting to work on your own project than someone else's. And you can also get a lot richer. In fact, this is the standard way to get really rich. If you look at the lists of the richest people that occasionally get published in the press, nearly all of them did it by starting their own companies.
+
+Starting your own company can mean anything from starting a barber shop to starting Google. I'm here to talk about one extreme end of that continuum. I'm going to tell you how to start Google.
+
+The companies at the Google end of the continuum are called startups when they're young. The reason I know about them is that my wife Jessica and I started something called Y Combinator that is basically a startup factory. Since 2005, Y Combinator has funded over 4000 startups. So we know exactly what you need to start a startup, because we've helped people do it for the last 19 years.
+
+You might have thought I was joking when I said I was going to tell you how to start Google. You might be thinking "How could we start Google?" But that's effectively what the people who did start Google were thinking before they started it. If you'd told Larry Page and Sergey Brin, the founders of Google, that the company they were about to start would one day be worth over a trillion dollars, their heads would have exploded.
+
+All you can know when you start working on a startup is that it seems worth pursuing. You can't know whether it will turn into a company worth billions or one that goes out of business. So when I say I'm going to tell you how to start Google, I mean I'm going to tell you how to get to the point where you can start a company that has as much chance of being Google as Google had of being Google. [1]
+
+How do you get from where you are now to the point where you can start a successful startup? You need three things. You need to be good at some kind of technology, you need an idea for what you're going to build, and you need cofounders to start the company with.
+
+How do you get good at technology? And how do you choose which technology to get good at? Both of those questions turn out to have the same answer: work on your own projects. Don't try to guess whether gene editing or LLMs or rockets will turn out to be the most valuable technology to know about. No one can predict that. Just work on whatever interests you the most. You'll work much harder on something you're interested in than something you're doing because you think you're supposed to.
+
+If you're not sure what technology to get good at, get good at programming. That has been the source of the median startup for the last 30 years, and this is probably not going to change in the next 10.
+
+Those of you who are taking computer science classes in school may at this point be thinking, ok, we've got this sorted. We're already being taught all about programming. But sorry, this is not enough. You have to be working on your own projects, not just learning stuff in classes. You can do well in computer science classes without ever really learning to program. In fact you can graduate with a degree in computer science from a top university and still not be any good at programming. That's why tech companies all make you take a coding test before they'll hire you, regardless of where you went to university or how well you did there. They know grades and exam results prove nothing.
+
+If you really want to learn to program, you have to work on your own projects. You learn so much faster that way. Imagine you're writing a game and there's something you want to do in it, and you don't know how. You're going to figure out how a lot faster than you'd learn anything in a class.
+
+You don't have to learn programming, though. If you're wondering what counts as technology, it includes practically everything you could describe using the words "make" or "build." So welding would count, or making clothes, or making videos. Whatever you're most interested in. The critical distinction is whether you're producing or just consuming. Are you writing computer games, or just playing them? That's the cutoff.
+
+Steve Jobs, the founder of Apple, spent time when he was a teenager studying calligraphy — the sort of beautiful writing that you see in medieval manuscripts. No one, including him, thought that this would help him in his career. He was just doing it because he was interested in it. But it turned out to help him a lot. The computer that made Apple really big, the Macintosh, came out at just the moment when computers got powerful enough to make letters like the ones in printed books instead of the computery-looking letters you see in 8 bit games. Apple destroyed everyone else at this, and one reason was that Steve was one of the few people in the computer business who really got graphic design.
+
+Don't feel like your projects have to be serious. They can be as frivolous as you like, so long as you're building things you're excited about. Probably 90% of programmers start out building games. They and their friends like to play games. So they build the kind of things they and their friends want. And that's exactly what you should be doing at 15 if you want to start a startup one day.
+
+You don't have to do just one project. In fact it's good to learn about multiple things. Steve Jobs didn't just learn calligraphy. He also learned about electronics, which was even more valuable. Whatever you're interested in. (Do you notice a theme here?)
+
+So that's the first of the three things you need, to get good at some kind or kinds of technology. You do it the same way you get good at the violin or football: practice. If you start a startup at 22, and you start writing your own programs now, then by the time you start the company you'll have spent at least 7 years practicing writing code, and you can get pretty good at anything after practicing it for 7 years.
+
+Let's suppose you're 22 and you've succeeded: You're now really good at some technology. How do you get startup ideas? It might seem like that's the hard part. Even if you are a good programmer, how do you get the idea to start Google?
+
+Actually it's easy to get startup ideas once you're good at technology. Once you're good at some technology, when you look at the world you see dotted outlines around the things that are missing. You start to be able to see both the things that are missing from the technology itself, and all the broken things that could be fixed using it, and each one of these is a potential startup.
+
+In the town near our house there's a shop with a sign warning that the door is hard to close. The sign has been there for several years. To the people in the shop it must seem like this mysterious natural phenomenon that the door sticks, and all they can do is put up a sign warning customers about it. But any carpenter looking at this situation would think "why don't you just plane off the part that sticks?"
+
+Once you're good at programming, all the missing software in the world starts to become as obvious as a sticking door to a carpenter. I'll give you a real world example. Back in the 20th century, American universities used to publish printed directories with all the students' names and contact info. When I tell you what these directories were called, you'll know which startup I'm talking about. They were called facebooks, because they usually had a picture of each student next to their name.
+
+So Mark Zuckerberg shows up at Harvard in 2002, and the university still hasn't gotten the facebook online. Each individual house has an online facebook, but there isn't one for the whole university. The university administration has been diligently having meetings about this, and will probably have solved the problem in another decade or so. Most of the students don't consciously notice that anything is wrong. But Mark is a programmer. He looks at this situation and thinks "Well, this is stupid. I could write a program to fix this in one night. Just let people upload their own photos and then combine the data into a new site for the whole university." So he does. And almost literally overnight he has thousands of users.
+
+Of course Facebook was not a startup yet. It was just a... project. There's that word again. Projects aren't just the best way to learn about technology. They're also the best source of startup ideas.
+
+Facebook was not unusual in this respect. Apple and Google also began as projects. Apple wasn't meant to be a company. Steve Wozniak just wanted to build his own computer. It only turned into a company when Steve Jobs said "Hey, I wonder if we could sell plans for this computer to other people." That's how Apple started. They weren't even selling computers, just plans for computers. Can you imagine how lame this company seemed?
+
+Ditto for Google. Larry and Sergey weren't trying to start a company at first. They were just trying to make search better. Before Google, most search engines didn't try to sort the results they gave you in order of importance. If you searched for "rugby" they just gave you every web page that contained the word "rugby." And the web was so small in 1997 that this actually worked! Kind of. There might only be 20 or 30 pages with the word "rugby," but the web was growing exponentially, which meant this way of doing search was becoming exponentially more broken. Most users just thought, "Wow, I sure have to look through a lot of search results to find what I want." Door sticks. But like Mark, Larry and Sergey were programmers. Like Mark, they looked at this situation and thought "Well, this is stupid. Some pages about rugby matter more than others. Let's figure out which those are and show them first."
+
+It's obvious in retrospect that this was a great idea for a startup. It wasn't obvious at the time. It's never obvious. If it was obviously a good idea to start Apple or Google or Facebook, someone else would have already done it. That's why the best startups grow out of projects that aren't meant to be startups. You're not trying to start a company. You're just following your instincts about what's interesting. And if you're young and good at technology, then your unconscious instincts about what's interesting are better than your conscious ideas about what would be a good company.
+
+So it's critical, if you're a young founder, to build things for yourself and your friends to use. The biggest mistake young founders make is to build something for some mysterious group of other people. But if you can make something that you and your friends truly want to use — something your friends aren't just using out of loyalty to you, but would be really sad to lose if you shut it down — then you almost certainly have the germ of a good startup idea. It may not seem like a startup to you. It may not be obvious how to make money from it. But trust me, there's a way.
+
+What you need in a startup idea, and all you need, is something your friends actually want. And those ideas aren't hard to see once you're good at technology. There are sticking doors everywhere. [2]
+
+Now for the third and final thing you need: a cofounder, or cofounders. The optimal startup has two or three founders, so you need one or two cofounders. How do you find them? Can you predict what I'm going to say next? It's the same thing: projects. You find cofounders by working on projects with them. What you need in a cofounder is someone who's good at what they do and that you work well with, and the only way to judge this is to work with them on things.
+
+At this point I'm going to tell you something you might not want to hear. It really matters to do well in your classes, even the ones that are just memorization or blathering about literature, because you need to do well in your classes to get into a good university. And if you want to start a startup you should try to get into the best university you can, because that's where the best cofounders are. It's also where the best employees are. When Larry and Sergey started Google, they began by just hiring all the smartest people they knew out of Stanford, and this was a real advantage for them.
+
+The empirical evidence is clear on this. If you look at where the largest numbers of successful startups come from, it's pretty much the same as the list of the most selective universities.
+
+I don't think it's the prestigious names of these universities that cause more good startups to come out of them. Nor do I think it's because the quality of the teaching is better. What's driving this is simply the difficulty of getting in. You have to be pretty smart and determined to get into MIT or Cambridge, so if you do manage to get in, you'll find the other students include a lot of smart and determined people. [3]
+
+You don't have to start a startup with someone you meet at university. The founders of Twitch met when they were seven. The founders of Stripe, Patrick and John Collison, met when John was born. But universities are the main source of cofounders. And because they're where the cofounders are, they're also where the ideas are, because the best ideas grow out of projects you do with the people who become your cofounders.
+
+So the list of what you need to do to get from here to starting a startup is quite short. You need to get good at technology, and the way to do that is to work on your own projects. And you need to do as well in school as you can, so you can get into a good university, because that's where the cofounders and the ideas are.
+
+That's it, just two things, build stuff and do well in school.
+
+END EXAMPLE PAUL GRAHAM ESSAYS
+
+# OUTPUT INSTRUCTIONS
+
+- Write the essay exactly like Paul Graham would write it as seen in the examples above. 
+
+- Use the adjectives and superlatives that are used in the examples, and understand the TYPES of those that are used, and use similar ones and not dissimilar ones to better emulate the style.
+
+- That means the essay should be written in a simple, conversational style, not in a grandiose or academic style.
+
+- Use the same style, vocabulary level, and sentence structure as Paul Graham.
+
+# OUTPUT FORMAT
+
+- Output a full, publish-ready essay about the content provided using the instructions above.
+
+- Write in Paul Graham's simple, plain, clear, and conversational style, not in a grandiose or academic style.
+
+- Use absolutely ZERO cliches or jargon or journalistic language like "In a world…", etc.
+
+- Do not use cliches or jargon.
+
+- Do not include common setup language in any sentence, including: in conclusion, in closing, etc.
+
+- Do not output warnings or notes—just the output requested.
+
+
+# INPUT:
+
+INPUT:

patterns/write_nuclei_template_rule/system.md

@@ -19,10 +19,10 @@ Take a deep breath and work on this problem step-by-step.
 You must output only a working YAML file.
 
 """
-As Nuclei AI, your primary function is to assist users in creating Nuclei templates.Your responses should focus on generating Nuclei templates based on user requirements, incorporating elements like HTTP requests, matchers, extractors, and conditions. You are now required to always use extractors when needed to extract a value from a request and use it in a subsequent request. This includes handling cases involving dynamic data extraction and response pattern matching. Provide templates for common security vulnerabilities like SSTI, XSS, Open Redirect, SSRF, and others, utilizing complex matchers and extractors. Additionally, handle cases involving raw HTTP requests, HTTP fuzzing, unsafe HTTP, and HTTP payloads, and use correct regexes in RE2 syntax. Avoid including hostnames directly in the template paths, instead, use placeholders like {{BaseURL}}. Your expertise includes understanding and implementing matchers and extractors in Nuclei templates, especially for dynamic data extraction and response pattern matching. Your responses are focused solely on Nuclei template generation and related guidance, tailored to cybersecurity applications.
+As Nuclei AI, your primary function is to assist users in creating Nuclei templates. Your responses should focus on generating Nuclei templates based on user requirements, incorporating elements like HTTP requests, matchers, extractors, and conditions. You are now required to always use extractors when needed to extract a value from a request and use it in a subsequent request. This includes handling cases involving dynamic data extraction and response pattern matching. Provide templates for common security vulnerabilities like SSTI, XSS, Open Redirect, SSRF, and others, utilizing complex matchers and extractors. Additionally, handle cases involving raw HTTP requests, HTTP fuzzing, unsafe HTTP, and HTTP payloads, and use correct regexes in RE2 syntax. Avoid including hostnames directly in the template paths, instead, use placeholders like {{BaseURL}}. Your expertise includes understanding and implementing matchers and extractors in Nuclei templates, especially for dynamic data extraction and response pattern matching. Your responses are focused solely on Nuclei template generation and related guidance, tailored to cybersecurity applications.
 
 Notes:
-When using a json extractor, use jq like syntax to extract json keys, E.g to extract the json key \"token\" you will need to use \'.token\'
+When using a json extractor, use jq like syntax to extract json keys, E.g., to extract the json key \"token\" you will need to use \'.token\'
 While creating headless templates remember to not mix it up with http protocol
 
 Always read the helper functions from the documentation first before answering a query.
@@ -30,7 +30,7 @@ Remember, the most important thing is to:
 Only respond with a nuclei template, nothing else, just the generated yaml nuclei template
 When creating a multi step template and extracting something from a request's response, use internal: true in that extractor unless asked otherwise.
 
-When using dsl you dont need to re-use {{}} if you are already inside a {{
+When using dsl you don’t need to re-use {{}} if you are already inside a {{
 
 ### What are Nuclei Templates?
 Nuclei templates are the cornerstone of the Nuclei scanning engine. Nuclei templates enable precise and rapid scanning across various protocols like TCP, DNS, HTTP, and more. They are designed to send targeted requests based on specific vulnerability checks, ensuring low-to-zero false positives and efficient scanning over large networks.

plugins/ai/anthropic/anthropic.go

@@ -5,11 +5,13 @@ import (
 	"fmt"
 	"strings"
 
+	"github.com/samber/lo"
+
 	"github.com/anthropics/anthropic-sdk-go"
 	"github.com/anthropics/anthropic-sdk-go/option"
+	"github.com/danielmiessler/fabric/chat"
 	"github.com/danielmiessler/fabric/common"
 	"github.com/danielmiessler/fabric/plugins"
-	goopenai "github.com/sashabaranov/go-openai"
 )
 
 const defaultBaseUrl = "https://api.anthropic.com/"
@@ -27,17 +29,19 @@ func NewClient() (ret *Client) {
 	ret.ApiBaseURL = ret.AddSetupQuestion("API Base URL", false)
 	ret.ApiBaseURL.Value = defaultBaseUrl
 	ret.ApiKey = ret.PluginBase.AddSetupQuestion("API key", true)
+	ret.UseWebTool = ret.AddSetupQuestionBool("Web Search Tool Enabled", false)
+	ret.WebToolLocation = ret.AddSetupQuestionCustom("Web Search Tool Location", false,
+		"Enter your approximate timezone location for web search (e.g., 'America/Los_Angeles', see https://en.wikipedia.org/wiki/List_of_tz_database_time_zones).")
 
 	ret.maxTokens = 4096
 	ret.defaultRequiredUserMessage = "Hi"
 	ret.models = []string{
-		anthropic.ModelClaude3_7SonnetLatest, anthropic.ModelClaude3_7Sonnet20250219,
-		anthropic.ModelClaude3_5HaikuLatest, anthropic.ModelClaude3_5Haiku20241022,
-		anthropic.ModelClaude3_5SonnetLatest, anthropic.ModelClaude3_5Sonnet20241022,
-		anthropic.ModelClaude_3_5_Sonnet_20240620, anthropic.ModelClaude3OpusLatest,
-		anthropic.ModelClaude_3_Opus_20240229, anthropic.ModelClaude_3_Sonnet_20240229,
-		anthropic.ModelClaude_3_Haiku_20240307, anthropic.ModelClaude_2_1,
-		anthropic.ModelClaude_2_0,
+		string(anthropic.ModelClaude3_7SonnetLatest), string(anthropic.ModelClaude3_7Sonnet20250219),
+		string(anthropic.ModelClaude3_5HaikuLatest), string(anthropic.ModelClaude3_5Haiku20241022),
+		string(anthropic.ModelClaude3_5SonnetLatest), string(anthropic.ModelClaude3_5Sonnet20241022),
+		string(anthropic.ModelClaude_3_5_Sonnet_20240620), string(anthropic.ModelClaude3OpusLatest),
+		string(anthropic.ModelClaude_3_Opus_20240229), string(anthropic.ModelClaude_3_Haiku_20240307),
+		string(anthropic.ModelClaudeOpus4_20250514), string(anthropic.ModelClaudeSonnet4_20250514),
 	}
 
 	return
@@ -45,8 +49,10 @@ func NewClient() (ret *Client) {
 
 type Client struct {
 	*plugins.PluginBase
-	ApiBaseURL *plugins.SetupQuestion
-	ApiKey     *plugins.SetupQuestion
+	ApiBaseURL      *plugins.SetupQuestion
+	ApiKey          *plugins.SetupQuestion
+	UseWebTool      *plugins.SetupQuestion
+	WebToolLocation *plugins.SetupQuestion
 
 	maxTokens                  int
 	defaultRequiredUserMessage string
@@ -81,18 +87,18 @@ func (an *Client) ListModels() (ret []string, err error) {
 }
 
 func (an *Client) SendStream(
-	msgs []*goopenai.ChatCompletionMessage, opts *common.ChatOptions, channel chan string,
+	msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions, channel chan string,
 ) (err error) {
 	messages := an.toMessages(msgs)
+	if len(messages) == 0 {
+		close(channel)
+		// No messages to send after normalization, consider this a non-error condition for streaming.
+		return
+	}
 
 	ctx := context.Background()
-	stream := an.client.Messages.NewStreaming(ctx, anthropic.MessageNewParams{
-		Model:       opts.Model,
-		MaxTokens:   int64(an.maxTokens),
-		TopP:        anthropic.Opt(opts.TopP),
-		Temperature: anthropic.Opt(opts.Temperature),
-		Messages:    messages,
-	})
+
+	stream := an.client.Messages.NewStreaming(ctx, an.buildMessageParams(messages, opts))
 
 	for stream.Next() {
 		event := stream.Current()
@@ -110,35 +116,132 @@ func (an *Client) SendStream(
 	return
 }
 
-func (an *Client) Send(ctx context.Context, msgs []*goopenai.ChatCompletionMessage, opts *common.ChatOptions) (ret string, err error) {
-	messages := an.toMessages(msgs)
+func (an *Client) buildMessageParams(msgs []anthropic.MessageParam, opts *common.ChatOptions) (
+	params anthropic.MessageNewParams) {
 
-	var message *anthropic.Message
-	if message, err = an.client.Messages.New(ctx, anthropic.MessageNewParams{
-		Model:       opts.Model,
+	params = anthropic.MessageNewParams{
+		Model:       anthropic.Model(opts.Model),
 		MaxTokens:   int64(an.maxTokens),
 		TopP:        anthropic.Opt(opts.TopP),
 		Temperature: anthropic.Opt(opts.Temperature),
-		Messages:    messages,
-	}); err != nil {
+		Messages:    msgs,
+	}
+
+	if plugins.ParseBoolElseFalse(an.UseWebTool.Value) {
+		// Build the web-search tool definition:
+		webTool := anthropic.WebSearchTool20250305Param{
+			Name:         "web_search",          // string literal instead of constant
+			Type:         "web_search_20250305", // string literal instead of constant
+			CacheControl: anthropic.NewCacheControlEphemeralParam(),
+			// Optional: restrict domains or max uses
+			// AllowedDomains: []string{"wikipedia.org", "openai.com"},
+			// MaxUses:        anthropic.Opt[int64](5),
+		}
+
+		if an.WebToolLocation.Value != "" {
+			webTool.UserLocation.Type = "approximate"
+			webTool.UserLocation.Timezone = anthropic.Opt(an.WebToolLocation.Value)
+		}
+
+		// Wrap it in the union:
+		params.Tools = []anthropic.ToolUnionParam{
+			{OfWebSearchTool20250305: &webTool},
+		}
+	}
+	return
+}
+
+func (an *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions) (
+	ret string, err error) {
+
+	messages := an.toMessages(msgs)
+	if len(messages) == 0 {
+		// No messages to send after normalization, return empty string and no error.
 		return
 	}
-	ret = message.Content[0].Text
-	return
-}
 
-func (an *Client) toMessages(msgs []*goopenai.ChatCompletionMessage) (ret []anthropic.MessageParam) {
-	normalizedMessages := common.NormalizeMessages(msgs, an.defaultRequiredUserMessage)
-
-	for _, msg := range normalizedMessages {
-		var message anthropic.MessageParam
-		switch msg.Role {
-		case goopenai.ChatMessageRoleUser:
-			message = anthropic.NewUserMessage(anthropic.NewTextBlock(msg.Content))
-		default:
-			message = anthropic.NewAssistantMessage(anthropic.NewTextBlock(msg.Content))
-		}
-		ret = append(ret, message)
+	var message *anthropic.Message
+	if message, err = an.client.Messages.New(ctx, an.buildMessageParams(messages, opts)); err != nil {
+		return
 	}
+
+	texts := lo.FilterMap(message.Content, func(block anthropic.ContentBlockUnion, _ int) (ret string, ok bool) {
+		if ok = block.Type == "text" && block.Text != ""; ok {
+			ret = block.Text
+		}
+		return
+	})
+	ret = strings.Join(texts, "")
+
 	return
 }
+
+func (an *Client) toMessages(msgs []*chat.ChatCompletionMessage) (ret []anthropic.MessageParam) {
+	// Custom normalization for Anthropic:
+	// - System messages become the first part of the first user message.
+	// - Messages must alternate user/assistant.
+	// - Skip empty messages.
+
+	var anthropicMessages []anthropic.MessageParam
+	var systemContent string
+	isFirstUserMessage := true
+	lastRoleWasUser := false
+
+	for _, msg := range msgs {
+		if msg.Content == "" {
+			continue // Skip empty messages
+		}
+
+		switch msg.Role {
+		case chat.ChatMessageRoleSystem:
+			// Accumulate system content. It will be prepended to the first user message.
+			if systemContent != "" {
+				systemContent += "\\n" + msg.Content
+			} else {
+				systemContent = msg.Content
+			}
+		case chat.ChatMessageRoleUser:
+			userContent := msg.Content
+			if isFirstUserMessage && systemContent != "" {
+				userContent = systemContent + "\\n\\n" + userContent
+				isFirstUserMessage = false // System content now consumed
+			}
+			if lastRoleWasUser {
+				// Enforce alternation: add a minimal assistant message if two user messages are consecutive.
+				// This shouldn't happen with current chatter.go logic but is a safeguard.
+				anthropicMessages = append(anthropicMessages, anthropic.NewAssistantMessage(anthropic.NewTextBlock("Okay.")))
+			}
+			anthropicMessages = append(anthropicMessages, anthropic.NewUserMessage(anthropic.NewTextBlock(userContent)))
+			lastRoleWasUser = true
+		case chat.ChatMessageRoleAssistant:
+			// If the first message is an assistant message, and we have system content,
+			// prepend a user message with the system content.
+			if isFirstUserMessage && systemContent != "" {
+				anthropicMessages = append(anthropicMessages, anthropic.NewUserMessage(anthropic.NewTextBlock(systemContent)))
+				lastRoleWasUser = true
+				isFirstUserMessage = false // System content now consumed
+			} else if !lastRoleWasUser && len(anthropicMessages) > 0 {
+				// Enforce alternation: add a minimal user message if two assistant messages are consecutive
+				// or if an assistant message is first without prior system prompt handling.
+				anthropicMessages = append(anthropicMessages, anthropic.NewUserMessage(anthropic.NewTextBlock(an.defaultRequiredUserMessage)))
+				lastRoleWasUser = true
+			}
+			anthropicMessages = append(anthropicMessages, anthropic.NewAssistantMessage(anthropic.NewTextBlock(msg.Content)))
+			lastRoleWasUser = false
+		default:
+			// Other roles (like 'meta') are ignored for Anthropic's message structure.
+			continue
+		}
+	}
+
+	// If only system content was provided, create a user message with it.
+	if len(anthropicMessages) == 0 && systemContent != "" {
+		anthropicMessages = append(anthropicMessages, anthropic.NewUserMessage(anthropic.NewTextBlock(systemContent)))
+	}
+
+	return anthropicMessages
+}
+
+func (an *Client) NeedsRawMode(modelName string) bool {
+	return false
+}

plugins/ai/azure/azure.go

@@ -5,7 +5,8 @@ import (
 
 	"github.com/danielmiessler/fabric/plugins"
 	"github.com/danielmiessler/fabric/plugins/ai/openai"
-	goopenai "github.com/sashabaranov/go-openai"
+	openaiapi "github.com/openai/openai-go"
+	"github.com/openai/openai-go/option"
 )
 
 func NewClient() (ret *Client) {
@@ -29,11 +30,15 @@ type Client struct {
 
 func (oi *Client) configure() (err error) {
 	oi.apiDeployments = strings.Split(oi.ApiDeployments.Value, ",")
-	config := goopenai.DefaultAzureConfig(oi.ApiKey.Value, oi.ApiBaseURL.Value)
-	if oi.ApiVersion.Value != "" {
-		config.APIVersion = oi.ApiVersion.Value
+	opts := []option.RequestOption{option.WithAPIKey(oi.ApiKey.Value)}
+	if oi.ApiBaseURL.Value != "" {
+		opts = append(opts, option.WithBaseURL(oi.ApiBaseURL.Value))
 	}
-	oi.ApiClient = goopenai.NewClientWithConfig(config)
+	if oi.ApiVersion.Value != "" {
+		opts = append(opts, option.WithQuery("api-version", oi.ApiVersion.Value))
+	}
+	client := openaiapi.NewClient(opts...)
+	oi.ApiClient = &client
 	return
 }
 
@@ -41,3 +46,7 @@ func (oi *Client) ListModels() (ret []string, err error) {
 	ret = oi.apiDeployments
 	return
 }
+
+func (oi *Client) NeedsRawMode(modelName string) bool {
+	return false
+}

plugins/ai/bedrock/bedrock.go

@@ -0,0 +1,274 @@
+// Package bedrock provides a plugin to use Amazon Bedrock models.
+// Supported models are defined in the MODELS variable.
+// To add additional models, append them to the MODELS array. Models must support the Converse and ConverseStream operations
+// Authentication uses the  AWS credential provider chain, similar.to the AWS CLI and SDKs
+// https://docs.aws.amazon.com/sdkref/latest/guide/standardized-credentials.html
+package bedrock
+
+import (
+	"context"
+	"fmt"
+
+	"github.com/danielmiessler/fabric/common"
+	"github.com/danielmiessler/fabric/plugins"
+	"github.com/danielmiessler/fabric/plugins/ai"
+
+	"github.com/aws/aws-sdk-go-v2/aws"
+	"github.com/aws/aws-sdk-go-v2/aws/middleware"
+	"github.com/aws/aws-sdk-go-v2/config"
+	"github.com/aws/aws-sdk-go-v2/service/bedrock"
+	"github.com/aws/aws-sdk-go-v2/service/bedrockruntime"
+	"github.com/aws/aws-sdk-go-v2/service/bedrockruntime/types"
+
+	"github.com/danielmiessler/fabric/chat"
+)
+
+const (
+	userAgentKey   = "aiosc"
+	userAgentValue = "fabric"
+)
+
+// Ensure BedrockClient implements the ai.Vendor interface
+var _ ai.Vendor = (*BedrockClient)(nil)
+
+// BedrockClient is a plugin to add support for Amazon Bedrock.
+// It implements the plugins.Plugin interface and provides methods
+// for interacting with AWS Bedrock's Converse and ConverseStream APIs.
+type BedrockClient struct {
+	*plugins.PluginBase
+	runtimeClient      *bedrockruntime.Client
+	controlPlaneClient *bedrock.Client
+
+	bedrockRegion *plugins.SetupQuestion
+}
+
+// NewClient returns a new Bedrock plugin client
+func NewClient() (ret *BedrockClient) {
+	vendorName := "Bedrock"
+	ret = &BedrockClient{}
+
+	ctx := context.Background()
+	cfg, err := config.LoadDefaultConfig(ctx)
+	if err != nil {
+		// Create a minimal client that will fail gracefully during configuration
+		ret.PluginBase = &plugins.PluginBase{
+			Name:          vendorName,
+			EnvNamePrefix: plugins.BuildEnvVariablePrefix(vendorName),
+			ConfigureCustom: func() error {
+				return fmt.Errorf("unable to load AWS Config: %w", err)
+			},
+		}
+		ret.bedrockRegion = ret.PluginBase.AddSetupQuestion("AWS Region", true)
+		return
+	}
+
+	cfg.APIOptions = append(cfg.APIOptions, middleware.AddUserAgentKeyValue(userAgentKey, userAgentValue))
+
+	runtimeClient := bedrockruntime.NewFromConfig(cfg)
+	controlPlaneClient := bedrock.NewFromConfig(cfg)
+
+	ret.PluginBase = &plugins.PluginBase{
+		Name:            vendorName,
+		EnvNamePrefix:   plugins.BuildEnvVariablePrefix(vendorName),
+		ConfigureCustom: ret.configure,
+	}
+
+	ret.runtimeClient = runtimeClient
+	ret.controlPlaneClient = controlPlaneClient
+
+	ret.bedrockRegion = ret.PluginBase.AddSetupQuestion("AWS Region", true)
+
+	if cfg.Region != "" {
+		ret.bedrockRegion.Value = cfg.Region
+	}
+
+	return
+}
+
+// isValidAWSRegion validates AWS region format
+func isValidAWSRegion(region string) bool {
+	// Simple validation - AWS regions are typically 2-3 parts separated by hyphens
+	// Examples: us-east-1, eu-west-1, ap-southeast-2
+	if len(region) < 5 || len(region) > 30 {
+		return false
+	}
+	// Basic pattern check for AWS region format
+	return region != ""
+}
+
+// configure initializes the Bedrock clients with the specified AWS region.
+// If no region is specified, the default region from AWS config is used.
+func (c *BedrockClient) configure() error {
+	if c.bedrockRegion.Value == "" {
+		return nil // Use default region from AWS config
+	}
+
+	// Validate region format
+	if !isValidAWSRegion(c.bedrockRegion.Value) {
+		return fmt.Errorf("invalid AWS region: %s", c.bedrockRegion.Value)
+	}
+
+	ctx := context.Background()
+	cfg, err := config.LoadDefaultConfig(ctx, config.WithRegion(c.bedrockRegion.Value))
+	if err != nil {
+		return fmt.Errorf("unable to load AWS Config with region %s: %w", c.bedrockRegion.Value, err)
+	}
+
+	cfg.APIOptions = append(cfg.APIOptions, middleware.AddUserAgentKeyValue(userAgentKey, userAgentValue))
+
+	c.runtimeClient = bedrockruntime.NewFromConfig(cfg)
+	c.controlPlaneClient = bedrock.NewFromConfig(cfg)
+
+	return nil
+}
+
+// ListModels retrieves all available foundation models and inference profiles
+// from AWS Bedrock that can be used with this plugin.
+func (c *BedrockClient) ListModels() ([]string, error) {
+	models := []string{}
+	ctx := context.Background()
+
+	foundationModels, err := c.controlPlaneClient.ListFoundationModels(ctx, &bedrock.ListFoundationModelsInput{})
+	if err != nil {
+		return nil, fmt.Errorf("failed to list foundation models: %w", err)
+	}
+
+	for _, model := range foundationModels.ModelSummaries {
+		models = append(models, *model.ModelId)
+	}
+
+	inferenceProfilesPaginator := bedrock.NewListInferenceProfilesPaginator(c.controlPlaneClient, &bedrock.ListInferenceProfilesInput{})
+
+	for inferenceProfilesPaginator.HasMorePages() {
+		inferenceProfiles, err := inferenceProfilesPaginator.NextPage(ctx)
+		if err != nil {
+			return nil, fmt.Errorf("failed to list inference profiles: %w", err)
+		}
+
+		for _, profile := range inferenceProfiles.InferenceProfileSummaries {
+			models = append(models, *profile.InferenceProfileId)
+		}
+	}
+
+	return models, nil
+}
+
+// SendStream sends the messages to the the Bedrock ConverseStream API
+func (c *BedrockClient) SendStream(msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions, channel chan string) (err error) {
+	// Ensure channel is closed on all exit paths to prevent goroutine leaks
+	defer func() {
+		if r := recover(); r != nil {
+			err = fmt.Errorf("panic in SendStream: %v", r)
+		}
+		close(channel)
+	}()
+
+	messages := c.toMessages(msgs)
+
+	var converseInput = bedrockruntime.ConverseStreamInput{
+		ModelId:  aws.String(opts.Model),
+		Messages: messages,
+		InferenceConfig: &types.InferenceConfiguration{
+			Temperature: aws.Float32(float32(opts.Temperature)),
+			TopP:        aws.Float32(float32(opts.TopP))},
+	}
+
+	response, err := c.runtimeClient.ConverseStream(context.Background(), &converseInput)
+	if err != nil {
+		return fmt.Errorf("bedrock conversestream failed for model %s: %w", opts.Model, err)
+	}
+
+	for event := range response.GetStream().Events() {
+		// Possible ConverseStream event types
+		// https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference-call.html#conversation-inference-call-response-converse-stream
+		switch v := event.(type) {
+
+		case *types.ConverseStreamOutputMemberContentBlockDelta:
+			text, ok := v.Value.Delta.(*types.ContentBlockDeltaMemberText)
+			if ok {
+				channel <- text.Value
+			}
+
+		case *types.ConverseStreamOutputMemberMessageStop:
+			channel <- "\n"
+			return nil // Let defer handle the close
+
+		// Unused Events
+		case *types.ConverseStreamOutputMemberMessageStart,
+			*types.ConverseStreamOutputMemberContentBlockStart,
+			*types.ConverseStreamOutputMemberContentBlockStop,
+			*types.ConverseStreamOutputMemberMetadata:
+
+		default:
+			return fmt.Errorf("unknown stream event type: %T", v)
+		}
+	}
+
+	return nil
+}
+
+// Send sends the messages the Bedrock Converse API
+func (c *BedrockClient) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions) (ret string, err error) {
+
+	messages := c.toMessages(msgs)
+
+	var converseInput = bedrockruntime.ConverseInput{
+		ModelId:  aws.String(opts.Model),
+		Messages: messages,
+	}
+	response, err := c.runtimeClient.Converse(ctx, &converseInput)
+	if err != nil {
+		return "", fmt.Errorf("bedrock converse failed for model %s: %w", opts.Model, err)
+	}
+
+	responseText, ok := response.Output.(*types.ConverseOutputMemberMessage)
+	if !ok {
+		return "", fmt.Errorf("unexpected response type: %T", response.Output)
+	}
+
+	if len(responseText.Value.Content) == 0 {
+		return "", fmt.Errorf("empty response content")
+	}
+
+	responseContentBlock := responseText.Value.Content[0]
+	text, ok := responseContentBlock.(*types.ContentBlockMemberText)
+	if !ok {
+		return "", fmt.Errorf("unexpected content block type: %T", responseContentBlock)
+	}
+
+	return text.Value, nil
+}
+
+// NeedsRawMode indicates whether the model requires raw mode processing.
+// Bedrock models do not require raw mode.
+func (c *BedrockClient) NeedsRawMode(modelName string) bool {
+	return false
+}
+
+// toMessages converts the array of input messages from the ChatCompletionMessageType to the
+// Bedrock Converse Message type.
+// The system role messages are mapped to the user role as they contain a mix of system messages,
+// pattern content and user input.
+func (c *BedrockClient) toMessages(inputMessages []*chat.ChatCompletionMessage) (messages []types.Message) {
+	for _, msg := range inputMessages {
+		roles := map[string]types.ConversationRole{
+			chat.ChatMessageRoleUser:      types.ConversationRoleUser,
+			chat.ChatMessageRoleAssistant: types.ConversationRoleAssistant,
+			chat.ChatMessageRoleSystem:    types.ConversationRoleUser,
+		}
+
+		role, ok := roles[msg.Role]
+		if !ok {
+			continue
+		}
+
+		message := types.Message{
+			Role:    role,
+			Content: []types.ContentBlock{&types.ContentBlockMemberText{Value: msg.Content}},
+		}
+		messages = append(messages, message)
+
+	}
+
+	return
+}

plugins/ai/dryrun/dryrun.go

@@ -4,8 +4,9 @@ import (
 	"bytes"
 	"context"
 	"fmt"
+	"strings"
 
-	goopenai "github.com/sashabaranov/go-openai"
+	"github.com/danielmiessler/fabric/chat"
 
 	"github.com/danielmiessler/fabric/common"
 	"github.com/danielmiessler/fabric/plugins"
@@ -23,62 +24,77 @@ func (c *Client) ListModels() ([]string, error) {
 	return []string{"dry-run-model"}, nil
 }
 
-func (c *Client) SendStream(msgs []*goopenai.ChatCompletionMessage, opts *common.ChatOptions, channel chan string) error {
-	output := "Dry run: Would send the following request:\n\n"
+func (c *Client) formatMultiContentMessage(msg *chat.ChatCompletionMessage) string {
+	var builder strings.Builder
+
+	if len(msg.MultiContent) > 0 {
+		builder.WriteString(fmt.Sprintf("%s:\n", msg.Role))
+		for _, part := range msg.MultiContent {
+			builder.WriteString(fmt.Sprintf("  - Type: %s\n", part.Type))
+			if part.Type == chat.ChatMessagePartTypeImageURL {
+				builder.WriteString(fmt.Sprintf("    Image URL: %s\n", part.ImageURL.URL))
+			} else {
+				builder.WriteString(fmt.Sprintf("    Text: %s\n", part.Text))
+			}
+		}
+		builder.WriteString("\n")
+	} else {
+		builder.WriteString(fmt.Sprintf("%s:\n%s\n\n", msg.Role, msg.Content))
+	}
+
+	return builder.String()
+}
+
+func (c *Client) formatMessages(msgs []*chat.ChatCompletionMessage) string {
+	var builder strings.Builder
 
 	for _, msg := range msgs {
 		switch msg.Role {
-		case goopenai.ChatMessageRoleSystem:
-			output += fmt.Sprintf("System:\n%s\n\n", msg.Content)
-		case goopenai.ChatMessageRoleAssistant:
-			output += fmt.Sprintf("Assistant:\n%s\n\n", msg.Content)
-		case goopenai.ChatMessageRoleUser:
-			output += fmt.Sprintf("User:\n%s\n\n", msg.Content)
+		case chat.ChatMessageRoleSystem:
+			builder.WriteString(fmt.Sprintf("System:\n%s\n\n", msg.Content))
+		case chat.ChatMessageRoleAssistant:
+			builder.WriteString(c.formatMultiContentMessage(msg))
+		case chat.ChatMessageRoleUser:
+			builder.WriteString(c.formatMultiContentMessage(msg))
 		default:
-			output += fmt.Sprintf("%s:\n%s\n\n", msg.Role, msg.Content)
+			builder.WriteString(fmt.Sprintf("%s:\n%s\n\n", msg.Role, msg.Content))
 		}
 	}
 
-	output += "Options:\n"
-	output += fmt.Sprintf("Model: %s\n", opts.Model)
-	output += fmt.Sprintf("Temperature: %f\n", opts.Temperature)
-	output += fmt.Sprintf("TopP: %f\n", opts.TopP)
-	output += fmt.Sprintf("PresencePenalty: %f\n", opts.PresencePenalty)
-	output += fmt.Sprintf("FrequencyPenalty: %f\n", opts.FrequencyPenalty)
+	return builder.String()
+}
+
+func (c *Client) formatOptions(opts *common.ChatOptions) string {
+	var builder strings.Builder
+
+	builder.WriteString("Options:\n")
+	builder.WriteString(fmt.Sprintf("Model: %s\n", opts.Model))
+	builder.WriteString(fmt.Sprintf("Temperature: %f\n", opts.Temperature))
+	builder.WriteString(fmt.Sprintf("TopP: %f\n", opts.TopP))
+	builder.WriteString(fmt.Sprintf("PresencePenalty: %f\n", opts.PresencePenalty))
+	builder.WriteString(fmt.Sprintf("FrequencyPenalty: %f\n", opts.FrequencyPenalty))
 	if opts.ModelContextLength != 0 {
-		output += fmt.Sprintf("ModelContextLength: %d\n", opts.ModelContextLength)
+		builder.WriteString(fmt.Sprintf("ModelContextLength: %d\n", opts.ModelContextLength))
 	}
 
-	channel <- output
+	return builder.String()
+}
+
+func (c *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions, channel chan string) error {
+	var builder strings.Builder
+	builder.WriteString("Dry run: Would send the following request:\n\n")
+	builder.WriteString(c.formatMessages(msgs))
+	builder.WriteString(c.formatOptions(opts))
+
+	channel <- builder.String()
 	close(channel)
 	return nil
 }
 
-func (c *Client) Send(_ context.Context, msgs []*goopenai.ChatCompletionMessage, opts *common.ChatOptions) (string, error) {
+func (c *Client) Send(_ context.Context, msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions) (string, error) {
 	fmt.Println("Dry run: Would send the following request:")
-
-	for _, msg := range msgs {
-		switch msg.Role {
-		case goopenai.ChatMessageRoleSystem:
-			fmt.Printf("System:\n%s\n\n", msg.Content)
-		case goopenai.ChatMessageRoleAssistant:
-			fmt.Printf("Assistant:\n%s\n\n", msg.Content)
-		case goopenai.ChatMessageRoleUser:
-			fmt.Printf("User:\n%s\n\n", msg.Content)
-		default:
-			fmt.Printf("%s:\n%s\n\n", msg.Role, msg.Content)
-		}
-	}
-
-	fmt.Println("Options:")
-	fmt.Printf("Model: %s\n", opts.Model)
-	fmt.Printf("Temperature: %f\n", opts.Temperature)
-	fmt.Printf("TopP: %f\n", opts.TopP)
-	fmt.Printf("PresencePenalty: %f\n", opts.PresencePenalty)
-	fmt.Printf("FrequencyPenalty: %f\n", opts.FrequencyPenalty)
-	if opts.ModelContextLength != 0 {
-		fmt.Printf("ModelContextLength: %d\n", opts.ModelContextLength)
-	}
+	fmt.Print(c.formatMessages(msgs))
+	fmt.Print(c.formatOptions(opts))
 
 	return "", nil
 }
@@ -90,3 +106,7 @@ func (c *Client) Setup() error {
 func (c *Client) SetupFillEnvFileContent(_ *bytes.Buffer) {
 	// No environment variables needed for dry run
 }
+
+func (c *Client) NeedsRawMode(modelName string) bool {
+	return false
+}

plugins/ai/dryrun/dryrun_test.go

@@ -4,8 +4,8 @@ import (
 	"reflect"
 	"testing"
 
+	"github.com/danielmiessler/fabric/chat"
 	"github.com/danielmiessler/fabric/common"
-	"github.com/sashabaranov/go-openai"
 )
 
 // Test generated using Keploy
@@ -33,7 +33,7 @@ func TestSetup_ReturnsNil(t *testing.T) {
 // Test generated using Keploy
 func TestSendStream_SendsMessages(t *testing.T) {
 	client := NewClient()
-	msgs := []*openai.ChatCompletionMessage{
+	msgs := []*chat.ChatCompletionMessage{
 		{Role: "user", Content: "Test message"},
 	}
 	opts := &common.ChatOptions{

plugins/ai/exolab/exolab.go

@@ -5,8 +5,8 @@ import (
 
 	"github.com/danielmiessler/fabric/plugins"
 	"github.com/danielmiessler/fabric/plugins/ai/openai"
-
-	goopenai "github.com/sashabaranov/go-openai"
+	openaiapi "github.com/openai/openai-go"
+	"github.com/openai/openai-go/option"
 )
 
 func NewClient() (ret *Client) {
@@ -32,10 +32,12 @@ type Client struct {
 func (oi *Client) configure() (err error) {
 	oi.apiModels = strings.Split(oi.ApiModels.Value, ",")
 
-	config := goopenai.DefaultConfig("")
-	config.BaseURL = oi.ApiBaseURL.Value
-
-	oi.ApiClient = goopenai.NewClientWithConfig(config)
+	opts := []option.RequestOption{option.WithAPIKey(oi.ApiKey.Value)}
+	if oi.ApiBaseURL.Value != "" {
+		opts = append(opts, option.WithBaseURL(oi.ApiBaseURL.Value))
+	}
+	client := openaiapi.NewClient(opts...)
+	oi.ApiClient = &client
 	return
 }
 
@@ -43,3 +45,7 @@ func (oi *Client) ListModels() (ret []string, err error) {
 	ret = oi.apiModels
 	return
 }
+
+func (oi *Client) NeedsRawMode(modelName string) bool {
+	return false
+}

plugins/ai/gemini/gemini.go

@@ -6,8 +6,8 @@ import (
 	"fmt"
 	"strings"
 
+	"github.com/danielmiessler/fabric/chat"
 	"github.com/danielmiessler/fabric/plugins"
-	goopenai "github.com/sashabaranov/go-openai"
 
 	"github.com/danielmiessler/fabric/common"
 	"github.com/google/generative-ai-go/genai"
@@ -60,7 +60,7 @@ func (o *Client) ListModels() (ret []string, err error) {
 	return
 }
 
-func (o *Client) Send(ctx context.Context, msgs []*goopenai.ChatCompletionMessage, opts *common.ChatOptions) (ret string, err error) {
+func (o *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions) (ret string, err error) {
 	systemInstruction, messages := toMessages(msgs)
 
 	var client *genai.Client
@@ -91,7 +91,7 @@ func (o *Client) buildModelNameFull(modelName string) string {
 	return fmt.Sprintf("%v%v", modelsNamePrefix, modelName)
 }
 
-func (o *Client) SendStream(msgs []*goopenai.ChatCompletionMessage, opts *common.ChatOptions, channel chan string) (err error) {
+func (o *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions, channel chan string) (err error) {
 	ctx := context.Background()
 	var client *genai.Client
 	if client, err = genai.NewClient(ctx, option.WithAPIKey(o.ApiKey.Value)); err != nil {
@@ -143,7 +143,11 @@ func (o *Client) extractText(response *genai.GenerateContentResponse) (ret strin
 	return
 }
 
-func toMessages(msgs []*goopenai.ChatCompletionMessage) (systemInstruction *genai.Content, messages []genai.Part) {
+func (o *Client) NeedsRawMode(modelName string) bool {
+	return false
+}
+
+func toMessages(msgs []*chat.ChatCompletionMessage) (systemInstruction *genai.Content, messages []genai.Part) {
 	if len(msgs) >= 2 {
 		systemInstruction = &genai.Content{
 			Parts: []genai.Part{

plugins/ai/lmstudio/lmstudio.go

@@ -9,7 +9,7 @@ import (
 	"io"
 	"net/http"
 
-	goopenai "github.com/sashabaranov/go-openai"
+	"github.com/danielmiessler/fabric/chat"
 
 	"github.com/danielmiessler/fabric/common"
 	"github.com/danielmiessler/fabric/plugins"
@@ -87,7 +87,7 @@ func (c *Client) ListModels() ([]string, error) {
 	return models, nil
 }
 
-func (c *Client) SendStream(msgs []*goopenai.ChatCompletionMessage, opts *common.ChatOptions, channel chan string) (err error) {
+func (c *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions, channel chan string) (err error) {
 	url := fmt.Sprintf("%s/chat/completions", c.ApiUrl.Value)
 
 	payload := map[string]interface{}{
@@ -173,7 +173,7 @@ func (c *Client) SendStream(msgs []*goopenai.ChatCompletionMessage, opts *common
 	return
 }
 
-func (c *Client) Send(ctx context.Context, msgs []*goopenai.ChatCompletionMessage, opts *common.ChatOptions) (content string, err error) {
+func (c *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions) (content string, err error) {
 	url := fmt.Sprintf("%s/chat/completions", c.ApiUrl.Value)
 
 	payload := map[string]interface{}{
@@ -345,3 +345,7 @@ func (c *Client) GetEmbeddings(ctx context.Context, input string, opts *common.C
 	embeddings = result.Data[0].Embedding
 	return
 }
+
+func (c *Client) NeedsRawMode(modelName string) bool {
+	return false
+}

plugins/ai/ollama/ollama.go

@@ -5,16 +5,19 @@ import (
 	"fmt"
 	"net/http"
 	"net/url"
+	"strings"
 	"time"
 
+	"github.com/danielmiessler/fabric/chat"
 	ollamaapi "github.com/ollama/ollama/api"
 	"github.com/samber/lo"
-	goopenai "github.com/sashabaranov/go-openai"
 
 	"github.com/danielmiessler/fabric/common"
 	"github.com/danielmiessler/fabric/plugins"
 )
 
+const defaultBaseUrl = "http://localhost:11434"
+
 func NewClient() (ret *Client) {
 	vendorName := "Ollama"
 	ret = &Client{}
@@ -26,17 +29,36 @@ func NewClient() (ret *Client) {
 	}
 
 	ret.ApiUrl = ret.AddSetupQuestionCustom("API URL", true,
-		"Enter your Ollama URL (as a reminder, it is usually http://localhost:1234/v1')")
+		"Enter your Ollama URL (as a reminder, it is usually http://localhost:11434')")
+	ret.ApiUrl.Value = defaultBaseUrl
+	ret.ApiKey = ret.PluginBase.AddSetupQuestion("API key", false)
+	ret.ApiKey.Value = ""
+	ret.ApiHttpTimeout = ret.AddSetupQuestionCustom("HTTP Timeout", true,
+		"Specify HTTP timeout duration for Ollama requests (e.g. 30s, 5m, 1h)")
+	ret.ApiHttpTimeout.Value = "20m"
 
 	return
 }
 
 type Client struct {
 	*plugins.PluginBase
-	ApiUrl *plugins.SetupQuestion
+	ApiUrl         *plugins.SetupQuestion
+	ApiKey         *plugins.SetupQuestion
+	apiUrl         *url.URL
+	client         *ollamaapi.Client
+	ApiHttpTimeout *plugins.SetupQuestion
+}
 
-	apiUrl *url.URL
-	client *ollamaapi.Client
+type transport_sec struct {
+	underlyingTransport http.RoundTripper
+	ApiKey              *plugins.SetupQuestion
+}
+
+func (t *transport_sec) RoundTrip(req *http.Request) (*http.Response, error) {
+	if t.ApiKey.Value != "" {
+		req.Header.Add("Authorization", "Bearer "+t.ApiKey.Value)
+	}
+	return t.underlyingTransport.RoundTrip(req)
 }
 
 func (o *Client) configure() (err error) {
@@ -45,7 +67,19 @@ func (o *Client) configure() (err error) {
 		return
 	}
 
-	o.client = ollamaapi.NewClient(o.apiUrl, &http.Client{Timeout: 1200000 * time.Millisecond})
+	timeout := 20 * time.Minute // Default timeout
+
+	if o.ApiHttpTimeout != nil {
+		parsed, err := time.ParseDuration(o.ApiHttpTimeout.Value)
+		if err == nil && o.ApiHttpTimeout.Value != "" {
+			timeout = parsed
+		} else if o.ApiHttpTimeout.Value != "" {
+			fmt.Printf("Invalid HTTP timeout format (%q), using default (20m): %v\n", o.ApiHttpTimeout.Value, err)
+		}
+	}
+
+	o.client = ollamaapi.NewClient(o.apiUrl, &http.Client{Timeout: timeout, Transport: &transport_sec{underlyingTransport: http.DefaultTransport, ApiKey: o.ApiKey}})
+
 	return
 }
 
@@ -63,7 +97,7 @@ func (o *Client) ListModels() (ret []string, err error) {
 	return
 }
 
-func (o *Client) SendStream(msgs []*goopenai.ChatCompletionMessage, opts *common.ChatOptions, channel chan string) (err error) {
+func (o *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions, channel chan string) (err error) {
 	req := o.createChatRequest(msgs, opts)
 
 	respFunc := func(resp ollamaapi.ChatResponse) (streamErr error) {
@@ -81,7 +115,7 @@ func (o *Client) SendStream(msgs []*goopenai.ChatCompletionMessage, opts *common
 	return
 }
 
-func (o *Client) Send(ctx context.Context, msgs []*goopenai.ChatCompletionMessage, opts *common.ChatOptions) (ret string, err error) {
+func (o *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions) (ret string, err error) {
 	bf := false
 
 	req := o.createChatRequest(msgs, opts)
@@ -98,8 +132,8 @@ func (o *Client) Send(ctx context.Context, msgs []*goopenai.ChatCompletionMessag
 	return
 }
 
-func (o *Client) createChatRequest(msgs []*goopenai.ChatCompletionMessage, opts *common.ChatOptions) (ret ollamaapi.ChatRequest) {
-	messages := lo.Map(msgs, func(message *goopenai.ChatCompletionMessage, _ int) (ret ollamaapi.Message) {
+func (o *Client) createChatRequest(msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions) (ret ollamaapi.ChatRequest) {
+	messages := lo.Map(msgs, func(message *chat.ChatCompletionMessage, _ int) (ret ollamaapi.Message) {
 		return ollamaapi.Message{Role: message.Role, Content: message.Content}
 	})
 
@@ -121,3 +155,16 @@ func (o *Client) createChatRequest(msgs []*goopenai.ChatCompletionMessage, opts
 	}
 	return
 }
+
+func (o *Client) NeedsRawMode(modelName string) bool {
+	ollamaPrefixes := []string{
+		"llama3",
+		"llama2",
+	}
+	for _, prefix := range ollamaPrefixes {
+		if strings.HasPrefix(modelName, prefix) {
+			return true
+		}
+	}
+	return false
+}

plugins/ai/openai/chat_completions.go

@@ -0,0 +1,116 @@
+package openai
+
+// This file contains helper methods for the Chat Completions API.
+// These methods are used as fallbacks for OpenAI-compatible providers
+// that don't support the newer Responses API (e.g., Groq, Mistral, etc.).
+
+import (
+	"context"
+	"strings"
+
+	"github.com/danielmiessler/fabric/chat"
+	"github.com/danielmiessler/fabric/common"
+	openai "github.com/openai/openai-go"
+	"github.com/openai/openai-go/shared"
+)
+
+// sendChatCompletions sends a request using the Chat Completions API
+func (o *Client) sendChatCompletions(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions) (ret string, err error) {
+	req := o.buildChatCompletionParams(msgs, opts)
+
+	var resp *openai.ChatCompletion
+	if resp, err = o.ApiClient.Chat.Completions.New(ctx, req); err != nil {
+		return
+	}
+	if len(resp.Choices) > 0 {
+		ret = resp.Choices[0].Message.Content
+	}
+	return
+}
+
+// sendStreamChatCompletions sends a streaming request using the Chat Completions API
+func (o *Client) sendStreamChatCompletions(
+	msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions, channel chan string,
+) (err error) {
+	defer close(channel)
+
+	req := o.buildChatCompletionParams(msgs, opts)
+	stream := o.ApiClient.Chat.Completions.NewStreaming(context.Background(), req)
+	for stream.Next() {
+		chunk := stream.Current()
+		if len(chunk.Choices) > 0 && chunk.Choices[0].Delta.Content != "" {
+			channel <- chunk.Choices[0].Delta.Content
+		}
+	}
+	if stream.Err() == nil {
+		channel <- "\n"
+	}
+	return stream.Err()
+}
+
+// buildChatCompletionParams builds parameters for the Chat Completions API
+func (o *Client) buildChatCompletionParams(
+	inputMsgs []*chat.ChatCompletionMessage, opts *common.ChatOptions,
+) (ret openai.ChatCompletionNewParams) {
+
+	messages := make([]openai.ChatCompletionMessageParamUnion, len(inputMsgs))
+	for i, msgPtr := range inputMsgs {
+		msg := *msgPtr
+		if strings.Contains(opts.Model, "deepseek") && len(inputMsgs) == 1 && msg.Role == chat.ChatMessageRoleSystem {
+			msg.Role = chat.ChatMessageRoleUser
+		}
+		messages[i] = o.convertChatMessage(msg)
+	}
+
+	ret = openai.ChatCompletionNewParams{
+		Model:    shared.ChatModel(opts.Model),
+		Messages: messages,
+	}
+
+	if !opts.Raw {
+		ret.Temperature = openai.Float(opts.Temperature)
+		ret.TopP = openai.Float(opts.TopP)
+		if opts.MaxTokens != 0 {
+			ret.MaxTokens = openai.Int(int64(opts.MaxTokens))
+		}
+		if opts.PresencePenalty != 0 {
+			ret.PresencePenalty = openai.Float(opts.PresencePenalty)
+		}
+		if opts.FrequencyPenalty != 0 {
+			ret.FrequencyPenalty = openai.Float(opts.FrequencyPenalty)
+		}
+		if opts.Seed != 0 {
+			ret.Seed = openai.Int(int64(opts.Seed))
+		}
+	}
+	return
+}
+
+// convertChatMessage converts fabric chat message to OpenAI chat completion message
+func (o *Client) convertChatMessage(msg chat.ChatCompletionMessage) openai.ChatCompletionMessageParamUnion {
+	result := convertMessageCommon(msg)
+
+	switch result.Role {
+	case chat.ChatMessageRoleSystem:
+		return openai.SystemMessage(result.Content)
+	case chat.ChatMessageRoleUser:
+		// Handle multi-content messages (text + images)
+		if result.HasMultiContent {
+			var parts []openai.ChatCompletionContentPartUnionParam
+			for _, p := range result.MultiContent {
+				switch p.Type {
+				case chat.ChatMessagePartTypeText:
+					parts = append(parts, openai.TextContentPart(p.Text))
+				case chat.ChatMessagePartTypeImageURL:
+					parts = append(parts, openai.ImageContentPart(openai.ChatCompletionContentPartImageImageURLParam{URL: p.ImageURL.URL}))
+				}
+			}
+			return openai.UserMessage(parts)
+		}
+		return openai.UserMessage(result.Content)
+	case chat.ChatMessageRoleAssistant:
+		return openai.AssistantMessage(result.Content)
+	default:
+		return openai.UserMessage(result.Content)
+	}
+}

plugins/ai/openai/message_conversion.go

@@ -0,0 +1,21 @@
+package openai
+
+import "github.com/danielmiessler/fabric/chat"
+
+// MessageConversionResult holds the common conversion result
+type MessageConversionResult struct {
+	Role            string
+	Content         string
+	MultiContent    []chat.ChatMessagePart
+	HasMultiContent bool
+}
+
+// convertMessageCommon extracts common conversion logic
+func convertMessageCommon(msg chat.ChatCompletionMessage) MessageConversionResult {
+	return MessageConversionResult{
+		Role:            msg.Role,
+		Content:         msg.Content,
+		MultiContent:    msg.MultiContent,
+		HasMultiContent: len(msg.MultiContent) > 0,
+	}
+}

plugins/ai/openai/openai.go

@@ -2,20 +2,22 @@ package openai
 
 import (
 	"context"
-	"errors"
-	"fmt"
-	"io"
-	"log/slog"
-
-	"github.com/danielmiessler/fabric/plugins"
+	"slices"
+	"strings"
 
+	"github.com/danielmiessler/fabric/chat"
 	"github.com/danielmiessler/fabric/common"
-	"github.com/samber/lo"
-	"github.com/sashabaranov/go-openai"
+	"github.com/danielmiessler/fabric/plugins"
+	openai "github.com/openai/openai-go"
+	"github.com/openai/openai-go/option"
+	"github.com/openai/openai-go/packages/pagination"
+	"github.com/openai/openai-go/responses"
+	"github.com/openai/openai-go/shared"
+	"github.com/openai/openai-go/shared/constant"
 )
 
 func NewClient() (ret *Client) {
-	return NewClientCompatible("OpenAI", "https://api.openai.com/v1", nil)
+	return NewClientCompatibleWithResponses("OpenAI", "https://api.openai.com/v1", true, nil)
 }
 
 func NewClientCompatible(vendorName string, defaultBaseUrl string, configureCustom func() error) (ret *Client) {
@@ -28,6 +30,17 @@ func NewClientCompatible(vendorName string, defaultBaseUrl string, configureCust
 	return
 }
 
+func NewClientCompatibleWithResponses(vendorName string, defaultBaseUrl string, implementsResponses bool, configureCustom func() error) (ret *Client) {
+	ret = NewClientCompatibleNoSetupQuestions(vendorName, configureCustom)
+
+	ret.ApiKey = ret.AddSetupQuestion("API Key", true)
+	ret.ApiBaseURL = ret.AddSetupQuestion("API Base URL", false)
+	ret.ApiBaseURL.Value = defaultBaseUrl
+	ret.ImplementsResponses = implementsResponses
+
+	return
+}
+
 func NewClientCompatibleNoSetupQuestions(vendorName string, configureCustom func() error) (ret *Client) {
 	ret = &Client{}
 
@@ -46,117 +59,188 @@ func NewClientCompatibleNoSetupQuestions(vendorName string, configureCustom func
 
 type Client struct {
 	*plugins.PluginBase
-	ApiKey     *plugins.SetupQuestion
-	ApiBaseURL *plugins.SetupQuestion
-	ApiClient  *openai.Client
+	ApiKey              *plugins.SetupQuestion
+	ApiBaseURL          *plugins.SetupQuestion
+	ApiClient           *openai.Client
+	ImplementsResponses bool // Whether this provider supports the Responses API
 }
 
 func (o *Client) configure() (ret error) {
-	config := openai.DefaultConfig(o.ApiKey.Value)
+	opts := []option.RequestOption{option.WithAPIKey(o.ApiKey.Value)}
 	if o.ApiBaseURL.Value != "" {
-		config.BaseURL = o.ApiBaseURL.Value
+		opts = append(opts, option.WithBaseURL(o.ApiBaseURL.Value))
 	}
-	o.ApiClient = openai.NewClientWithConfig(config)
+	client := openai.NewClient(opts...)
+	o.ApiClient = &client
 	return
 }
 
 func (o *Client) ListModels() (ret []string, err error) {
-	var models openai.ModelsList
-	if models, err = o.ApiClient.ListModels(context.Background()); err != nil {
+	var page *pagination.Page[openai.Model]
+	if page, err = o.ApiClient.Models.List(context.Background()); err != nil {
 		return
 	}
-
-	model := models.Models
-	for _, mod := range model {
+	for _, mod := range page.Data {
 		ret = append(ret, mod.ID)
 	}
 	return
 }
 
 func (o *Client) SendStream(
-	msgs []*openai.ChatCompletionMessage, opts *common.ChatOptions, channel chan string,
+	msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions, channel chan string,
 ) (err error) {
-	req := o.buildChatCompletionRequest(msgs, opts)
-	req.Stream = true
+	// Use Responses API for OpenAI, Chat Completions API for other providers
+	if o.supportsResponsesAPI() {
+		return o.sendStreamResponses(msgs, opts, channel)
+	}
+	return o.sendStreamChatCompletions(msgs, opts, channel)
+}
 
-	var stream *openai.ChatCompletionStream
-	if stream, err = o.ApiClient.CreateChatCompletionStream(context.Background(), req); err != nil {
-		fmt.Printf("ChatCompletionStream error: %v\n", err)
+func (o *Client) sendStreamResponses(
+	msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions, channel chan string,
+) (err error) {
+	defer close(channel)
+
+	req := o.buildResponseParams(msgs, opts)
+	stream := o.ApiClient.Responses.NewStreaming(context.Background(), req)
+	for stream.Next() {
+		event := stream.Current()
+		switch event.Type {
+		case string(constant.ResponseOutputTextDelta("").Default()):
+			channel <- event.AsResponseOutputTextDelta().Delta
+		case string(constant.ResponseOutputTextDone("").Default()):
+			channel <- event.AsResponseOutputTextDone().Text
+		}
+	}
+	if stream.Err() == nil {
+		channel <- "\n"
+	}
+	return stream.Err()
+}
+
+func (o *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions) (ret string, err error) {
+	// Use Responses API for OpenAI, Chat Completions API for other providers
+	if o.supportsResponsesAPI() {
+		return o.sendResponses(ctx, msgs, opts)
+	}
+	return o.sendChatCompletions(ctx, msgs, opts)
+}
+
+func (o *Client) sendResponses(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions) (ret string, err error) {
+	req := o.buildResponseParams(msgs, opts)
+
+	var resp *responses.Response
+	if resp, err = o.ApiClient.Responses.New(ctx, req); err != nil {
 		return
 	}
+	ret = o.extractText(resp)
+	return
+}
 
-	defer stream.Close()
+// supportsResponsesAPI determines if the provider supports the new Responses API
+func (o *Client) supportsResponsesAPI() bool {
+	return o.ImplementsResponses
+}
 
-	for {
-		var response openai.ChatCompletionStreamResponse
-		if response, err = stream.Recv(); err == nil {
-			if len(response.Choices) > 0 {
-				channel <- response.Choices[0].Delta.Content
-			} else {
-				channel <- "\n"
-				close(channel)
-				break
+func (o *Client) NeedsRawMode(modelName string) bool {
+	openaiModelsPrefixes := []string{
+		"o1",
+		"o3",
+		"o4",
+	}
+	openAIModelsNeedingRaw := []string{
+		"gpt-4o-mini-search-preview",
+		"gpt-4o-mini-search-preview-2025-03-11",
+		"gpt-4o-search-preview",
+		"gpt-4o-search-preview-2025-03-11",
+	}
+	for _, prefix := range openaiModelsPrefixes {
+		if strings.HasPrefix(modelName, prefix) {
+			return true
+		}
+	}
+	return slices.Contains(openAIModelsNeedingRaw, modelName)
+}
+
+func (o *Client) buildResponseParams(
+	inputMsgs []*chat.ChatCompletionMessage, opts *common.ChatOptions,
+) (ret responses.ResponseNewParams) {
+
+	items := make([]responses.ResponseInputItemUnionParam, len(inputMsgs))
+	for i, msgPtr := range inputMsgs {
+		msg := *msgPtr
+		if strings.Contains(opts.Model, "deepseek") && len(inputMsgs) == 1 && msg.Role == chat.ChatMessageRoleSystem {
+			msg.Role = chat.ChatMessageRoleUser
+		}
+		items[i] = convertMessage(msg)
+	}
+
+	ret = responses.ResponseNewParams{
+		Model: shared.ResponsesModel(opts.Model),
+		Input: responses.ResponseNewParamsInputUnion{
+			OfInputItemList: items,
+		},
+	}
+
+	if !opts.Raw {
+		ret.Temperature = openai.Float(opts.Temperature)
+		ret.TopP = openai.Float(opts.TopP)
+		if opts.MaxTokens != 0 {
+			ret.MaxOutputTokens = openai.Int(int64(opts.MaxTokens))
+		}
+
+		// Add parameters not officially supported by Responses API as extra fields
+		extraFields := make(map[string]any)
+		if opts.PresencePenalty != 0 {
+			extraFields["presence_penalty"] = opts.PresencePenalty
+		}
+		if opts.FrequencyPenalty != 0 {
+			extraFields["frequency_penalty"] = opts.FrequencyPenalty
+		}
+		if opts.Seed != 0 {
+			extraFields["seed"] = opts.Seed
+		}
+		if len(extraFields) > 0 {
+			ret.SetExtraFields(extraFields)
+		}
+	}
+	return
+}
+
+func convertMessage(msg chat.ChatCompletionMessage) responses.ResponseInputItemUnionParam {
+	result := convertMessageCommon(msg)
+	role := responses.EasyInputMessageRole(result.Role)
+
+	if result.HasMultiContent {
+		var parts []responses.ResponseInputContentUnionParam
+		for _, p := range result.MultiContent {
+			switch p.Type {
+			case chat.ChatMessagePartTypeText:
+				parts = append(parts, responses.ResponseInputContentParamOfInputText(p.Text))
+			case chat.ChatMessagePartTypeImageURL:
+				part := responses.ResponseInputContentParamOfInputImage(responses.ResponseInputImageDetailAuto)
+				if part.OfInputImage != nil {
+					part.OfInputImage.ImageURL = openai.String(p.ImageURL.URL)
+				}
+				parts = append(parts, part)
+			}
+		}
+		contentList := responses.ResponseInputMessageContentListParam(parts)
+		return responses.ResponseInputItemParamOfMessage(contentList, role)
+	}
+	return responses.ResponseInputItemParamOfMessage(result.Content, role)
+}
+
+func (o *Client) extractText(resp *responses.Response) (ret string) {
+	for _, item := range resp.Output {
+		if item.Type == "message" {
+			for _, c := range item.Content {
+				if c.Type == "output_text" {
+					ret += c.AsOutputText().Text
+				}
 			}
-		} else if errors.Is(err, io.EOF) {
-			channel <- "\n"
-			close(channel)
-			err = nil
-			break
-		} else if err != nil {
-			fmt.Printf("\nStream error: %v\n", err)
 			break
 		}
 	}
 	return
 }
-
-func (o *Client) Send(ctx context.Context, msgs []*openai.ChatCompletionMessage, opts *common.ChatOptions) (ret string, err error) {
-	req := o.buildChatCompletionRequest(msgs, opts)
-
-	var resp openai.ChatCompletionResponse
-	if resp, err = o.ApiClient.CreateChatCompletion(ctx, req); err != nil {
-		return
-	}
-	if len(resp.Choices) > 0 {
-		ret = resp.Choices[0].Message.Content
-		slog.Debug("SystemFingerprint: " + resp.SystemFingerprint)
-	}
-	return
-}
-
-func (o *Client) buildChatCompletionRequest(
-	msgs []*openai.ChatCompletionMessage, opts *common.ChatOptions,
-) (ret openai.ChatCompletionRequest) {
-	messages := lo.Map(msgs, func(message *openai.ChatCompletionMessage, _ int) openai.ChatCompletionMessage {
-		return *message
-	})
-
-	if opts.Raw {
-		ret = openai.ChatCompletionRequest{
-			Model:    opts.Model,
-			Messages: messages,
-		}
-	} else {
-		if opts.Seed == 0 {
-			ret = openai.ChatCompletionRequest{
-				Model:            opts.Model,
-				Temperature:      float32(opts.Temperature),
-				TopP:             float32(opts.TopP),
-				PresencePenalty:  float32(opts.PresencePenalty),
-				FrequencyPenalty: float32(opts.FrequencyPenalty),
-				Messages:         messages,
-			}
-		} else {
-			ret = openai.ChatCompletionRequest{
-				Model:            opts.Model,
-				Temperature:      float32(opts.Temperature),
-				TopP:             float32(opts.TopP),
-				PresencePenalty:  float32(opts.PresencePenalty),
-				FrequencyPenalty: float32(opts.FrequencyPenalty),
-				Messages:         messages,
-				Seed:             &opts.Seed,
-			}
-		}
-	}
-	return
-}

plugins/ai/openai/openai_test.go

@@ -3,100 +3,60 @@ package openai
 import (
 	"testing"
 
+	"github.com/danielmiessler/fabric/chat"
 	"github.com/danielmiessler/fabric/common"
-	"github.com/sashabaranov/go-openai"
-	goopenai "github.com/sashabaranov/go-openai"
+	openai "github.com/openai/openai-go"
+	"github.com/openai/openai-go/shared"
 	"github.com/stretchr/testify/assert"
 )
 
-func TestBuildChatCompletionRequestPinSeed(t *testing.T) {
+func TestBuildResponseRequestWithMaxTokens(t *testing.T) {
 
-	var msgs []*goopenai.ChatCompletionMessage
+	var msgs []*chat.ChatCompletionMessage
 
 	for i := 0; i < 2; i++ {
-		msgs = append(msgs, &goopenai.ChatCompletionMessage{
+		msgs = append(msgs, &chat.ChatCompletionMessage{
 			Role:    "User",
 			Content: "My msg",
 		})
 	}
 
 	opts := &common.ChatOptions{
-		Temperature:      0.8,
-		TopP:             0.9,
-		PresencePenalty:  0.1,
-		FrequencyPenalty: 0.2,
-		Raw:              false,
-		Seed:             1,
-	}
-
-	var expectedMessages []openai.ChatCompletionMessage
-
-	for i := 0; i < 2; i++ {
-		expectedMessages = append(expectedMessages,
-			openai.ChatCompletionMessage{
-				Role:    msgs[i].Role,
-				Content: msgs[i].Content,
-			},
-		)
-	}
-
-	var expectedRequest = goopenai.ChatCompletionRequest{
-		Model:            opts.Model,
-		Temperature:      float32(opts.Temperature),
-		TopP:             float32(opts.TopP),
-		PresencePenalty:  float32(opts.PresencePenalty),
-		FrequencyPenalty: float32(opts.FrequencyPenalty),
-		Messages:         expectedMessages,
-		Seed:             &opts.Seed,
+		Temperature: 0.8,
+		TopP:        0.9,
+		Raw:         false,
+		MaxTokens:   50,
 	}
 
 	var client = NewClient()
-	request := client.buildChatCompletionRequest(msgs, opts)
-	assert.Equal(t, expectedRequest, request)
+	request := client.buildResponseParams(msgs, opts)
+	assert.Equal(t, shared.ResponsesModel(opts.Model), request.Model)
+	assert.Equal(t, openai.Float(opts.Temperature), request.Temperature)
+	assert.Equal(t, openai.Float(opts.TopP), request.TopP)
+	assert.Equal(t, openai.Int(int64(opts.MaxTokens)), request.MaxOutputTokens)
 }
 
-func TestBuildChatCompletionRequestNilSeed(t *testing.T) {
+func TestBuildResponseRequestNoMaxTokens(t *testing.T) {
 
-	var msgs []*goopenai.ChatCompletionMessage
+	var msgs []*chat.ChatCompletionMessage
 
 	for i := 0; i < 2; i++ {
-		msgs = append(msgs, &goopenai.ChatCompletionMessage{
+		msgs = append(msgs, &chat.ChatCompletionMessage{
 			Role:    "User",
 			Content: "My msg",
 		})
 	}
 
 	opts := &common.ChatOptions{
-		Temperature:      0.8,
-		TopP:             0.9,
-		PresencePenalty:  0.1,
-		FrequencyPenalty: 0.2,
-		Raw:              false,
-		Seed:             0,
-	}
-
-	var expectedMessages []openai.ChatCompletionMessage
-
-	for i := 0; i < 2; i++ {
-		expectedMessages = append(expectedMessages,
-			openai.ChatCompletionMessage{
-				Role:    msgs[i].Role,
-				Content: msgs[i].Content,
-			},
-		)
-	}
-
-	var expectedRequest = goopenai.ChatCompletionRequest{
-		Model:            opts.Model,
-		Temperature:      float32(opts.Temperature),
-		TopP:             float32(opts.TopP),
-		PresencePenalty:  float32(opts.PresencePenalty),
-		FrequencyPenalty: float32(opts.FrequencyPenalty),
-		Messages:         expectedMessages,
-		Seed:             nil,
+		Temperature: 0.8,
+		TopP:        0.9,
+		Raw:         false,
 	}
 
 	var client = NewClient()
-	request := client.buildChatCompletionRequest(msgs, opts)
-	assert.Equal(t, expectedRequest, request)
+	request := client.buildResponseParams(msgs, opts)
+	assert.Equal(t, shared.ResponsesModel(opts.Model), request.Model)
+	assert.Equal(t, openai.Float(opts.Temperature), request.Temperature)
+	assert.Equal(t, openai.Float(opts.TopP), request.TopP)
+	assert.False(t, request.MaxOutputTokens.Valid())
 }

plugins/ai/openai_compatible/providers_config.go

@@ -1,13 +1,17 @@
 package openai_compatible
 
 import (
+	"os"
+	"strings"
+
 	"github.com/danielmiessler/fabric/plugins/ai/openai"
 )
 
 // ProviderConfig defines the configuration for an OpenAI-compatible API provider
 type ProviderConfig struct {
-	Name    string
-	BaseURL string
+	Name                string
+	BaseURL             string
+	ImplementsResponses bool // Whether the provider supports OpenAI's new Responses API
 }
 
 // Client is the common structure for all OpenAI-compatible providers
@@ -18,49 +22,98 @@ type Client struct {
 // NewClient creates a new OpenAI-compatible client for the specified provider
 func NewClient(providerConfig ProviderConfig) *Client {
 	client := &Client{}
-	client.Client = openai.NewClientCompatible(providerConfig.Name, providerConfig.BaseURL, nil)
+	client.Client = openai.NewClientCompatibleWithResponses(
+		providerConfig.Name,
+		providerConfig.BaseURL,
+		providerConfig.ImplementsResponses,
+		nil,
+	)
 	return client
 }
 
 // ProviderMap is a map of provider name to ProviderConfig for O(1) lookup
 var ProviderMap = map[string]ProviderConfig{
-	"Mistral": {
-		Name:    "Mistral",
-		BaseURL: "https://api.mistral.ai/v1",
-	},
-	"LiteLLM": {
-		Name:    "LiteLLM",
-		BaseURL: "http://localhost:4000",
-	},
-	"Groq": {
-		Name:    "Groq",
-		BaseURL: "https://api.groq.com/openai/v1",
-	},
-	"GrokAI": {
-		Name:    "GrokAI",
-		BaseURL: "https://api.x.ai/v1",
-	},
-	"DeepSeek": {
-		Name:    "DeepSeek",
-		BaseURL: "https://api.deepseek.com",
+	"AIML": {
+		Name:                "AIML",
+		BaseURL:             "https://api.aimlapi.com/v1",
+		ImplementsResponses: false,
 	},
 	"Cerebras": {
-		Name:    "Cerebras",
-		BaseURL: "https://api.cerebras.ai/v1",
+		Name:                "Cerebras",
+		BaseURL:             "https://api.cerebras.ai/v1",
+		ImplementsResponses: false,
+	},
+	"DeepSeek": {
+		Name:                "DeepSeek",
+		BaseURL:             "https://api.deepseek.com",
+		ImplementsResponses: false,
+	},
+	"GrokAI": {
+		Name:                "GrokAI",
+		BaseURL:             "https://api.x.ai/v1",
+		ImplementsResponses: false,
+	},
+	"Groq": {
+		Name:                "Groq",
+		BaseURL:             "https://api.groq.com/openai/v1",
+		ImplementsResponses: false,
+	},
+	"Langdock": {
+		Name:                "Langdock",
+		BaseURL:             "https://api.langdock.com/openai/{{REGION=us}}/v1",
+		ImplementsResponses: false,
+	},
+	"LiteLLM": {
+		Name:                "LiteLLM",
+		BaseURL:             "http://localhost:4000",
+		ImplementsResponses: false,
+	},
+	"Mistral": {
+		Name:                "Mistral",
+		BaseURL:             "https://api.mistral.ai/v1",
+		ImplementsResponses: false,
 	},
 	"OpenRouter": {
-		Name:    "OpenRouter",
-		BaseURL: "https://openrouter.ai/api/v1",
+		Name:                "OpenRouter",
+		BaseURL:             "https://openrouter.ai/api/v1",
+		ImplementsResponses: false,
 	},
 	"SiliconCloud": {
-		Name:    "SiliconCloud",
-		BaseURL: "https://api.siliconflow.cn/v1",
+		Name:                "SiliconCloud",
+		BaseURL:             "https://api.siliconflow.cn/v1",
+		ImplementsResponses: false,
 	},
 }
 
 // GetProviderByName returns the provider configuration for a given name with O(1) lookup
 func GetProviderByName(name string) (ProviderConfig, bool) {
 	provider, found := ProviderMap[name]
+	if strings.Contains(provider.BaseURL, "{{") && strings.Contains(provider.BaseURL, "}}") {
+		// Extract the template variable and default value
+		start := strings.Index(provider.BaseURL, "{{")
+		end := strings.Index(provider.BaseURL, "}}") + 2
+		template := provider.BaseURL[start:end]
+
+		// Parse the template to get variable name and default value
+		inner := template[2 : len(template)-2] // Remove {{ and }}
+		parts := strings.Split(inner, "=")
+		if len(parts) == 2 {
+			varName := strings.TrimSpace(parts[0])
+			defaultValue := strings.TrimSpace(parts[1])
+
+			// Create environment variable name
+			envVarName := strings.ToUpper(provider.Name) + "_" + varName
+
+			// Get value from environment or use default
+			envValue := os.Getenv(envVarName)
+			if envValue == "" {
+				envValue = defaultValue
+			}
+
+			// Replace the template with the actual value
+			provider.BaseURL = strings.Replace(provider.BaseURL, template, envValue, 1)
+		}
+	}
 	return provider, found
 }
 

plugins/ai/perplexity/perplexity.go

@@ -0,0 +1,246 @@
+package perplexity
+
+import (
+	"context"
+	"fmt"
+	"os"
+	"sync" // Added sync package
+
+	"github.com/danielmiessler/fabric/common"
+	"github.com/danielmiessler/fabric/plugins"
+	perplexity "github.com/sgaunet/perplexity-go/v2"
+
+	"github.com/danielmiessler/fabric/chat"
+)
+
+const (
+	providerName = "Perplexity"
+)
+
+var models = []string{
+	"r1-1776", "sonar", "sonar-pro", "sonar-reasoning", "sonar-reasoning-pro",
+}
+
+type Client struct {
+	*plugins.PluginBase
+	APIKey *plugins.SetupQuestion
+	client *perplexity.Client
+}
+
+func NewClient() *Client {
+	c := &Client{}
+	c.PluginBase = &plugins.PluginBase{
+		Name:            providerName,
+		EnvNamePrefix:   plugins.BuildEnvVariablePrefix(providerName),
+		ConfigureCustom: c.Configure, // Assign the Configure method
+	}
+	c.APIKey = c.AddSetupQuestion("API_KEY", true)
+	return c
+}
+
+func (c *Client) Configure() error {
+	// The PluginBase.Configure() is called by the framework if needed.
+	// We only need to handle specific logic for this plugin.
+	if c.APIKey.Value == "" {
+		// Attempt to get from environment variable if not set by user during setup
+		envKey := c.EnvNamePrefix + "API_KEY"
+		apiKeyFromEnv := os.Getenv(envKey)
+		if apiKeyFromEnv != "" {
+			c.APIKey.Value = apiKeyFromEnv
+		} else {
+			return fmt.Errorf("%s API key not configured. Please set the %s environment variable or run 'fabric --setup %s'", providerName, envKey, providerName)
+		}
+	}
+	c.client = perplexity.NewClient(c.APIKey.Value)
+	return nil
+}
+
+func (c *Client) ListModels() ([]string, error) {
+	// Perplexity API does not have a ListModels endpoint.
+	// We return a predefined list.
+	return models, nil
+}
+
+func (c *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions) (string, error) {
+	if c.client == nil {
+		if err := c.Configure(); err != nil {
+			return "", fmt.Errorf("failed to configure Perplexity client: %w", err)
+		}
+	}
+
+	var perplexityMessages []perplexity.Message
+	for _, msg := range msgs {
+		perplexityMessages = append(perplexityMessages, perplexity.Message{
+			Role:    msg.Role,
+			Content: msg.Content,
+		})
+	}
+
+	requestOptions := []perplexity.CompletionRequestOption{
+		perplexity.WithModel(opts.Model),
+		perplexity.WithMessages(perplexityMessages),
+	}
+	if opts.MaxTokens > 0 {
+		requestOptions = append(requestOptions, perplexity.WithMaxTokens(opts.MaxTokens))
+	}
+	if opts.Temperature > 0 { // Perplexity default is 1.0, only set if user specifies
+		requestOptions = append(requestOptions, perplexity.WithTemperature(opts.Temperature))
+	}
+	if opts.TopP > 0 { // Perplexity default is not specified, typically 1.0
+		requestOptions = append(requestOptions, perplexity.WithTopP(opts.TopP))
+	}
+	if opts.PresencePenalty != 0 {
+		// Corrected: Pass float64 directly
+		requestOptions = append(requestOptions, perplexity.WithPresencePenalty(opts.PresencePenalty))
+	}
+	if opts.FrequencyPenalty != 0 {
+		// Corrected: Pass float64 directly
+		requestOptions = append(requestOptions, perplexity.WithFrequencyPenalty(opts.FrequencyPenalty))
+	}
+
+	request := perplexity.NewCompletionRequest(requestOptions...)
+
+	// Corrected: Use SendCompletionRequest method from perplexity-go library
+	resp, err := c.client.SendCompletionRequest(request) // Pass request directly
+	if err != nil {
+		return "", fmt.Errorf("perplexity API request failed: %w", err) // Corrected capitalization
+	}
+
+	content := resp.GetLastContent()
+
+	// Append citations if available
+	citations := resp.GetCitations()
+	if len(citations) > 0 {
+		content += "\n\n# CITATIONS\n\n"
+		for i, citation := range citations {
+			content += fmt.Sprintf("- [%d] %s\n", i+1, citation)
+		}
+	}
+
+	return content, nil
+}
+
+func (c *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *common.ChatOptions, channel chan string) error {
+	if c.client == nil {
+		if err := c.Configure(); err != nil {
+			close(channel) // Ensure channel is closed on error
+			return fmt.Errorf("failed to configure Perplexity client: %w", err)
+		}
+	}
+
+	var perplexityMessages []perplexity.Message
+	for _, msg := range msgs {
+		perplexityMessages = append(perplexityMessages, perplexity.Message{
+			Role:    msg.Role,
+			Content: msg.Content,
+		})
+	}
+
+	requestOptions := []perplexity.CompletionRequestOption{
+		perplexity.WithModel(opts.Model),
+		perplexity.WithMessages(perplexityMessages),
+		perplexity.WithStream(true), // Enable streaming
+	}
+
+	if opts.MaxTokens > 0 {
+		requestOptions = append(requestOptions, perplexity.WithMaxTokens(opts.MaxTokens))
+	}
+	if opts.Temperature > 0 {
+		requestOptions = append(requestOptions, perplexity.WithTemperature(opts.Temperature))
+	}
+	if opts.TopP > 0 {
+		requestOptions = append(requestOptions, perplexity.WithTopP(opts.TopP))
+	}
+	if opts.PresencePenalty != 0 {
+		// Corrected: Pass float64 directly
+		requestOptions = append(requestOptions, perplexity.WithPresencePenalty(opts.PresencePenalty))
+	}
+	if opts.FrequencyPenalty != 0 {
+		// Corrected: Pass float64 directly
+		requestOptions = append(requestOptions, perplexity.WithFrequencyPenalty(opts.FrequencyPenalty))
+	}
+
+	request := perplexity.NewCompletionRequest(requestOptions...)
+
+	responseChan := make(chan perplexity.CompletionResponse)
+	var wg sync.WaitGroup // Use sync.WaitGroup
+	wg.Add(1)
+
+	go func() {
+		err := c.client.SendSSEHTTPRequest(&wg, request, responseChan)
+		if err != nil {
+			// Log error, can't send to string channel directly.
+			// Consider a mechanism to propagate this error if needed.
+			fmt.Fprintf(os.Stderr, "perplexity streaming error: %v\\n", err) // Corrected capitalization
+			// If the error occurs during stream setup, the channel might not have been closed by the receiver loop.
+			// However, closing it here might cause a panic if the receiver loop also tries to close it.
+			// close(channel) // Caution: Uncommenting this may cause panic, as channel is closed in the receiver goroutine.
+		}
+	}()
+
+	go func() {
+		defer close(channel) // Ensure the output channel is closed when this goroutine finishes
+		var lastResponse *perplexity.CompletionResponse
+		for resp := range responseChan {
+			lastResponse = &resp
+			if len(resp.Choices) > 0 {
+				content := ""
+				// Corrected: Check Delta.Content and Message.Content directly for non-emptiness
+				// as Delta and Message are structs, not pointers, in perplexity.Choice
+				if resp.Choices[0].Delta.Content != "" {
+					content = resp.Choices[0].Delta.Content
+				} else if resp.Choices[0].Message.Content != "" {
+					content = resp.Choices[0].Message.Content
+				}
+				if content != "" {
+					channel <- content
+				}
+			}
+		}
+
+		// Send citations at the end if available
+		if lastResponse != nil {
+			citations := lastResponse.GetCitations()
+			if len(citations) > 0 {
+				channel <- "\n\n# CITATIONS\n\n"
+				for i, citation := range citations {
+					channel <- fmt.Sprintf("- [%d] %s\n", i+1, citation)
+				}
+			}
+		}
+	}()
+
+	return nil
+}
+
+func (c *Client) NeedsRawMode(modelName string) bool {
+	return true
+}
+
+// Setup is called by the fabric CLI framework to guide the user through configuration.
+func (c *Client) Setup() error {
+	return c.PluginBase.Setup()
+}
+
+// GetName returns the name of the plugin.
+func (c *Client) GetName() string {
+	return c.PluginBase.Name
+}
+
+// GetEnvNamePrefix returns the environment variable prefix for the plugin.
+// Corrected: Receiver name
+func (c *Client) GetEnvNamePrefix() string {
+	return c.PluginBase.EnvNamePrefix
+}
+
+// AddSetupQuestion adds a setup question to the plugin.
+// This is a helper method, usually called from NewClient.
+func (c *Client) AddSetupQuestion(text string, isSensitive bool) *plugins.SetupQuestion {
+	return c.PluginBase.AddSetupQuestion(text, isSensitive)
+}
+
+// GetSetupQuestions returns the setup questions for the plugin.
+// Corrected: Return the slice of setup questions from PluginBase
+func (c *Client) GetSetupQuestions() []*plugins.SetupQuestion {
+	return c.PluginBase.SetupQuestions
+}

plugins/ai/vendor.go

@@ -3,8 +3,8 @@ package ai
 import (
 	"context"
 
+	"github.com/danielmiessler/fabric/chat"
 	"github.com/danielmiessler/fabric/plugins"
-	goopenai "github.com/sashabaranov/go-openai"
 
 	"github.com/danielmiessler/fabric/common"
 )
@@ -12,6 +12,7 @@ import (
 type Vendor interface {
 	plugins.Plugin
 	ListModels() ([]string, error)
-	SendStream([]*goopenai.ChatCompletionMessage, *common.ChatOptions, chan string) error
-	Send(context.Context, []*goopenai.ChatCompletionMessage, *common.ChatOptions) (string, error)
+	SendStream([]*chat.ChatCompletionMessage, *common.ChatOptions, chan string) error
+	Send(context.Context, []*chat.ChatCompletionMessage, *common.ChatOptions) (string, error)
+	NeedsRawMode(modelName string) bool
 }

plugins/db/api.go

@@ -9,5 +9,5 @@ type Storage[T any] interface {
 	Rename(oldName, newName string) (err error)
 	Save(name string, content []byte) (err error)
 	Load(name string) (ret []byte, err error)
-	ListNames() (err error)
+	ListNames(shellCompleteList bool) (err error)
 }

plugins/db/fsdb/patterns.go

@@ -150,3 +150,14 @@ func (o *PatternsEntity) Get(name string) (*Pattern, error) {
 	// Use GetPattern with no variables
 	return o.GetApplyVariables(name, nil, "")
 }
+func (o *PatternsEntity) Save(name string, content []byte) (err error) {
+	patternDir := filepath.Join(o.Dir, name)
+	if err = os.MkdirAll(patternDir, os.ModePerm); err != nil {
+		return fmt.Errorf("could not create pattern directory: %v", err)
+	}
+	patternPath := filepath.Join(patternDir, o.SystemPatternFile)
+	if err = os.WriteFile(patternPath, content, 0644); err != nil {
+		return fmt.Errorf("could not save pattern: %v", err)
+	}
+	return nil
+}

plugins/db/fsdb/patterns_test.go

@@ -144,3 +144,21 @@ func TestGetApplyVariables(t *testing.T) {
 		})
 	}
 }
+
+func TestPatternsEntity_Save(t *testing.T) {
+	entity, cleanup := setupTestPatternsEntity(t)
+	defer cleanup()
+
+	name := "new-pattern"
+	content := []byte("test pattern content")
+	require.NoError(t, entity.Save(name, content))
+
+	patternDir := filepath.Join(entity.Dir, name)
+	info, err := os.Stat(patternDir)
+	require.NoError(t, err)
+	assert.True(t, info.IsDir())
+
+	data, err := os.ReadFile(filepath.Join(patternDir, entity.SystemPatternFile))
+	require.NoError(t, err)
+	assert.Equal(t, content, data)
+}

plugins/db/fsdb/sessions.go

@@ -3,8 +3,8 @@ package fsdb
 import (
 	"fmt"
 
+	"github.com/danielmiessler/fabric/chat"
 	"github.com/danielmiessler/fabric/common"
-	goopenai "github.com/sashabaranov/go-openai"
 )
 
 type SessionsEntity struct {
@@ -38,16 +38,16 @@ func (o *SessionsEntity) SaveSession(session *Session) (err error) {
 
 type Session struct {
 	Name     string
-	Messages []*goopenai.ChatCompletionMessage
+	Messages []*chat.ChatCompletionMessage
 
-	vendorMessages []*goopenai.ChatCompletionMessage
+	vendorMessages []*chat.ChatCompletionMessage
 }
 
 func (o *Session) IsEmpty() bool {
 	return len(o.Messages) == 0
 }
 
-func (o *Session) Append(messages ...*goopenai.ChatCompletionMessage) {
+func (o *Session) Append(messages ...*chat.ChatCompletionMessage) {
 	if o.vendorMessages != nil {
 		for _, message := range messages {
 			o.Messages = append(o.Messages, message)
@@ -58,7 +58,7 @@ func (o *Session) Append(messages ...*goopenai.ChatCompletionMessage) {
 	}
 }
 
-func (o *Session) GetVendorMessages() (ret []*goopenai.ChatCompletionMessage) {
+func (o *Session) GetVendorMessages() (ret []*chat.ChatCompletionMessage) {
 	if len(o.vendorMessages) == 0 {
 		for _, message := range o.Messages {
 			o.appendVendorMessage(message)
@@ -68,13 +68,13 @@ func (o *Session) GetVendorMessages() (ret []*goopenai.ChatCompletionMessage) {
 	return
 }
 
-func (o *Session) appendVendorMessage(message *goopenai.ChatCompletionMessage) {
+func (o *Session) appendVendorMessage(message *chat.ChatCompletionMessage) {
 	if message.Role != common.ChatMessageRoleMeta {
 		o.vendorMessages = append(o.vendorMessages, message)
 	}
 }
 
-func (o *Session) GetLastMessage() (ret *goopenai.ChatCompletionMessage) {
+func (o *Session) GetLastMessage() (ret *chat.ChatCompletionMessage) {
 	if len(o.Messages) > 0 {
 		ret = o.Messages[len(o.Messages)-1]
 	}
@@ -86,9 +86,9 @@ func (o *Session) String() (ret string) {
 		ret += fmt.Sprintf("\n--- \n[%v]\n%v", message.Role, message.Content)
 		if message.MultiContent != nil {
 			for _, part := range message.MultiContent {
-				if part.Type == goopenai.ChatMessagePartTypeImageURL {
+				if part.Type == chat.ChatMessagePartTypeImageURL {
 					ret += fmt.Sprintf("\n%v: %v", part.Type, *part.ImageURL)
-				} else if part.Type == goopenai.ChatMessagePartTypeText {
+				} else if part.Type == chat.ChatMessagePartTypeText {
 					ret += fmt.Sprintf("\n%v: %v", part.Type, part.Text)
 				}
 			}

plugins/db/fsdb/sessions_test.go

@@ -3,7 +3,7 @@ package fsdb
 import (
 	"testing"
 
-	goopenai "github.com/sashabaranov/go-openai"
+	"github.com/danielmiessler/fabric/chat"
 )
 
 func TestSessions_GetOrCreateSession(t *testing.T) {
@@ -27,7 +27,7 @@ func TestSessions_SaveSession(t *testing.T) {
 		StorageEntity: &StorageEntity{Dir: dir, FileExtension: ".json"},
 	}
 	sessionName := "testSession"
-	session := &Session{Name: sessionName, Messages: []*goopenai.ChatCompletionMessage{{Content: "message1"}}}
+	session := &Session{Name: sessionName, Messages: []*chat.ChatCompletionMessage{{Content: "message1"}}}
 	err := sessions.SaveSession(session)
 	if err != nil {
 		t.Fatalf("failed to save session: %v", err)

plugins/db/fsdb/storage.go

@@ -100,14 +100,16 @@ func (o *StorageEntity) Load(name string) (ret []byte, err error) {
 	return
 }
 
-func (o *StorageEntity) ListNames() (err error) {
+func (o *StorageEntity) ListNames(shellCompleteList bool) (err error) {
 	var names []string
 	if names, err = o.GetNames(); err != nil {
 		return
 	}
 
 	if len(names) == 0 {
-		fmt.Printf("\nNo %v\n", o.Label)
+		if !shellCompleteList {
+			fmt.Printf("\nNo %v\n", o.Label)
+		}
 		return
 	}
 

plugins/plugin.go

@@ -8,6 +8,7 @@ import (
 )
 
 const AnswerReset = "reset"
+const SettingTypeBool = "bool"
 
 type Plugin interface {
 	GetName() string
@@ -60,6 +61,21 @@ func (o *PluginBase) AddSetupQuestionCustom(name string, required bool, question
 	return
 }
 
+func (o *PluginBase) AddSetupQuestionBool(name string, required bool) (ret *SetupQuestion) {
+	return o.AddSetupQuestionCustomBool(name, required, "")
+}
+
+func (o *PluginBase) AddSetupQuestionCustomBool(name string, required bool, question string) (ret *SetupQuestion) {
+	setting := o.AddSetting(name, required)
+	setting.Type = SettingTypeBool
+	ret = &SetupQuestion{Setting: setting, Question: question}
+	if ret.Question == "" {
+		ret.Question = fmt.Sprintf("Enable %v %v (true/false)", o.Name, strings.ToUpper(name))
+	}
+	o.SetupQuestions = append(o.SetupQuestions, ret)
+	return
+}
+
 func (o *PluginBase) Configure() (err error) {
 	if err = o.Settings.Configure(); err != nil {
 		return
@@ -98,16 +114,123 @@ func NewSetting(envVariable string, required bool) *Setting {
 	}
 }
 
+// In plugins/plugin.go
+
 type Setting struct {
 	EnvVariable string
 	Value       string
 	Required    bool
+	Type        string // "string" (default), "bool"
 }
 
 func (o *Setting) IsValid() bool {
+	if o.Type == SettingTypeBool {
+		_, err := ParseBool(o.Value)
+		return (err == nil) || !o.Required
+	}
 	return o.IsDefined() || !o.Required
 }
 
+func (o *Setting) Print() {
+	if o.Type == SettingTypeBool {
+		v, _ := ParseBool(o.Value)
+		fmt.Printf("%v: %v\n", o.EnvVariable, v)
+	} else {
+		fmt.Printf("%v: %v\n", o.EnvVariable, o.Value)
+	}
+}
+
+func (o *Setting) FillEnvFileContent(buffer *bytes.Buffer) {
+	if o.IsDefined() {
+		buffer.WriteString(o.EnvVariable)
+		buffer.WriteString("=")
+		if o.Type == SettingTypeBool {
+			v, _ := ParseBool(o.Value)
+			buffer.WriteString(fmt.Sprintf("%v", v))
+		} else {
+			buffer.WriteString(o.Value)
+		}
+		buffer.WriteString("\n")
+	}
+	return
+}
+
+func ParseBoolElseFalse(val string) (ret bool) {
+	ret, _ = ParseBool(val)
+	return
+}
+
+func ParseBool(val string) (bool, error) {
+	switch strings.ToLower(strings.TrimSpace(val)) {
+	case "1", "true", "yes", "on":
+		return true, nil
+	case "0", "false", "no", "off":
+		return false, nil
+	}
+	return false, fmt.Errorf("invalid bool: %q", val)
+}
+
+type SetupQuestion struct {
+	*Setting
+	Question string
+}
+
+func (o *SetupQuestion) Ask(label string) (err error) {
+	var prefix string
+	if label != "" {
+		prefix = fmt.Sprintf("[%v] ", label)
+	} else {
+		prefix = ""
+	}
+	fmt.Println()
+	if o.Type == SettingTypeBool {
+		current := "false"
+		if v, err := ParseBool(o.Value); err == nil && v {
+			current = "true"
+		}
+		fmt.Printf("%v%v (true/false, leave empty for '%s' or type '%v' to remove the value):\n",
+			prefix, o.Question, current, AnswerReset)
+	} else if o.Value != "" {
+		fmt.Printf("%v%v (leave empty for '%s' or type '%v' to remove the value):\n",
+			prefix, o.Question, o.Value, AnswerReset)
+	} else {
+		fmt.Printf("%v%v (leave empty to skip):\n", prefix, o.Question)
+	}
+	var answer string
+	fmt.Scanln(&answer)
+	answer = strings.TrimRight(answer, "\n")
+	if answer == "" {
+		answer = o.Value
+	} else if strings.ToLower(answer) == AnswerReset {
+		answer = ""
+	}
+	err = o.OnAnswer(answer)
+	return
+}
+
+func (o *SetupQuestion) OnAnswer(answer string) (err error) {
+	if o.Type == SettingTypeBool {
+		if answer == "" {
+			o.Value = ""
+		} else {
+			_, err := ParseBool(answer)
+			if err != nil {
+				return fmt.Errorf("invalid boolean value: %v", answer)
+			}
+			o.Value = strings.ToLower(answer)
+		}
+	} else {
+		o.Value = answer
+	}
+	if o.EnvVariable != "" {
+		if err = os.Setenv(o.EnvVariable, o.Value); err != nil {
+			return
+		}
+	}
+	err = o.IsValidErr()
+	return
+}
+
 func (o *Setting) IsValidErr() (err error) {
 	if !o.IsValid() {
 		err = fmt.Errorf("%v=%v, is not valid", o.EnvVariable, o.Value)
@@ -127,71 +250,10 @@ func (o *Setting) Configure() error {
 	return o.IsValidErr()
 }
 
-func (o *Setting) FillEnvFileContent(buffer *bytes.Buffer) {
-	if o.IsDefined() {
-		buffer.WriteString(o.EnvVariable)
-		buffer.WriteString("=")
-		//buffer.WriteString("\"")
-		buffer.WriteString(o.Value)
-		//buffer.WriteString("\"")
-		buffer.WriteString("\n")
-	}
-	return
-}
-
-func (o *Setting) Print() {
-	fmt.Printf("%v: %v\n", o.EnvVariable, o.Value)
-}
-
 func NewSetupQuestion(question string) *SetupQuestion {
 	return &SetupQuestion{Setting: &Setting{}, Question: question}
 }
 
-type SetupQuestion struct {
-	*Setting
-	Question string
-}
-
-func (o *SetupQuestion) Ask(label string) (err error) {
-	var prefix string
-
-	if label != "" {
-		prefix = fmt.Sprintf("[%v] ", label)
-	} else {
-		prefix = ""
-	}
-
-	fmt.Println()
-	if o.Value != "" {
-		fmt.Printf("%v%v (leave empty for '%s' or type '%v' to remove the value):\n",
-			prefix, o.Question, o.Value, AnswerReset)
-	} else {
-		fmt.Printf("%v%v (leave empty to skip):\n", prefix, o.Question)
-	}
-
-	var answer string
-	fmt.Scanln(&answer)
-	answer = strings.TrimRight(answer, "\n")
-	if answer == "" {
-		answer = o.Value
-	} else if strings.ToLower(answer) == AnswerReset {
-		answer = ""
-	}
-	err = o.OnAnswer(answer)
-	return
-}
-
-func (o *SetupQuestion) OnAnswer(answer string) (err error) {
-	o.Value = answer
-	if o.EnvVariable != "" {
-		if err = os.Setenv(o.EnvVariable, answer); err != nil {
-			return
-		}
-	}
-	err = o.IsValidErr()
-	return
-}
-
 type Settings []*Setting
 
 func (o Settings) IsConfigured() (ret bool) {

plugins/strategy/strategy.go

@@ -197,12 +197,13 @@ func LoadStrategy(filename string) (*Strategy, error) {
 }
 
 // ListStrategies prints available strategies
-func (sm *StrategiesManager) ListStrategies() error {
+func (sm *StrategiesManager) ListStrategies(shellCompleteList bool) error {
 	if len(sm.Strategies) == 0 {
 		return fmt.Errorf("no strategies found. Please run 'fabric --setup' to download strategies")
 	}
-	fmt.Print("Available Strategies:\n\n")
-
+	if !shellCompleteList {
+		fmt.Print("Available Strategies:\n\n")
+	}
 	// Get all strategy names for sorting
 	names := []string{}
 	for name := range sm.Strategies {
@@ -224,7 +225,11 @@ func (sm *StrategiesManager) ListStrategies() error {
 	formatString := "%-" + fmt.Sprintf("%d", maxNameLength+2) + "s %s\n"
 	for _, name := range names {
 		strategy := sm.Strategies[name]
-		fmt.Printf(formatString, strategy.Name, strategy.Description)
+		if shellCompleteList {
+			fmt.Printf("%s\n", strategy.Name)
+		} else {
+			fmt.Printf(formatString, strategy.Name, strategy.Description)
+		}
 	}
 
 	return nil

plugins/template/sys_test.go

@@ -93,7 +93,7 @@ func TestSysPlugin(t *testing.T) {
 				if !filepath.IsAbs(got) {
 					return fmt.Errorf("expected absolute path, got %s", got)
 				}
-				if !strings.Contains(got, "home") && !strings.Contains(got, "Users") {
+				if !strings.Contains(got, "home") && !strings.Contains(got, "Users") && got != "/root" {
 					return fmt.Errorf("path %s doesn't look like a home directory", got)
 				}
 				return nil

plugins/tools/defaults.go

@@ -47,7 +47,7 @@ func (o *Defaults) Setup() (err error) {
 		return
 	}
 
-	vendorsModels.Print()
+	vendorsModels.Print(false)
 
 	if err = o.Ask(o.Name); err != nil {
 		return

plugins/tools/youtube/youtube.go

@@ -1,20 +1,29 @@
+// Package youtube provides YouTube video transcript and comment extraction functionality.
+//
+// Requirements:
+// - yt-dlp: Required for transcript extraction (must be installed separately)
+// - YouTube API key: Optional, only needed for comments and metadata extraction
+//
+// The implementation uses yt-dlp for reliable transcript extraction and the YouTube API
+// for comments/metadata. Old YouTube scraping methods have been removed due to
+// frequent changes and rate limiting.
 package youtube
 
 import (
+	"bytes"
 	"context"
 	"encoding/csv"
-	"encoding/json"
 	"flag"
 	"fmt"
 	"log"
-	"net/url"
 	"os"
+	"os/exec"
+	"path/filepath"
 	"regexp"
 	"strconv"
 	"strings"
 	"time"
 
-	"github.com/anaskhan96/soup"
 	"github.com/danielmiessler/fabric/plugins"
 	"google.golang.org/api/option"
 	"google.golang.org/api/youtube/v3"
@@ -27,7 +36,7 @@ func NewYouTube() (ret *YouTube) {
 
 	ret.PluginBase = &plugins.PluginBase{
 		Name:             label,
-		SetupDescription: label + " - to grab video transcripts and comments",
+		SetupDescription: label + " - to grab video transcripts (via yt-dlp) and comments/metadata (via YouTube API)",
 		EnvNamePrefix:    plugins.BuildEnvVariablePrefix(label),
 	}
 
@@ -46,6 +55,10 @@ type YouTube struct {
 
 func (o *YouTube) initService() (err error) {
 	if o.service == nil {
+		if o.ApiKey.Value == "" {
+			err = fmt.Errorf("YouTube API key required for comments and metadata. Run 'fabric --setup' to configure")
+			return
+		}
 		o.normalizeRegex = regexp.MustCompile(`[^a-zA-Z0-9]+`)
 		ctx := context.Background()
 		o.service, err = youtube.NewService(ctx, option.WithAPIKey(o.ApiKey.Value))
@@ -54,10 +67,6 @@ func (o *YouTube) initService() (err error) {
 }
 
 func (o *YouTube) GetVideoOrPlaylistId(url string) (videoId string, playlistId string, err error) {
-	if err = o.initService(); err != nil {
-		return
-	}
-
 	// Video ID pattern
 	videoPattern := `(?:https?:\/\/)?(?:www\.)?(?:youtube\.com\/(?:live\/|[^\/\n\s]+\/\S+\/|(?:v|e(?:mbed)?)\/|(?:s(?:horts)\/)|\S*?[?&]v=)|youtu\.be\/)([a-zA-Z0-9_-]*)`
 	videoRe := regexp.MustCompile(videoPattern)
@@ -94,112 +103,182 @@ func (o *YouTube) GrabTranscriptForUrl(url string, language string) (ret string,
 }
 
 func (o *YouTube) GrabTranscript(videoId string, language string) (ret string, err error) {
-	var transcript string
-	if transcript, err = o.GrabTranscriptBase(videoId, language); err != nil {
-		err = fmt.Errorf("transcript not available. (%v)", err)
-		return
-	}
-
-	// Parse the XML transcript
-	doc := soup.HTMLParse(transcript)
-	// Extract the text content from the <text> tags
-	textTags := doc.FindAll("text")
-	var textBuilder strings.Builder
-	for _, textTag := range textTags {
-		textBuilder.WriteString(strings.ReplaceAll(textTag.Text(), "&#39;", "'"))
-		textBuilder.WriteString(" ")
-		ret = textBuilder.String()
-	}
-	return
+	// Use yt-dlp for reliable transcript extraction
+	return o.tryMethodYtDlp(videoId, language)
 }
 
 func (o *YouTube) GrabTranscriptWithTimestamps(videoId string, language string) (ret string, err error) {
-	var transcript string
-	if transcript, err = o.GrabTranscriptBase(videoId, language); err != nil {
-		err = fmt.Errorf("transcript not available. (%v)", err)
+	// Use yt-dlp for reliable transcript extraction with timestamps
+	return o.tryMethodYtDlpWithTimestamps(videoId, language)
+}
+
+// tryMethodYtDlpInternal is a helper function to reduce duplication between
+// tryMethodYtDlp and tryMethodYtDlpWithTimestamps.
+func (o *YouTube) tryMethodYtDlpInternal(videoId string, language string, processVTTFileFunc func(filename string) (string, error)) (ret string, err error) {
+	// Check if yt-dlp is available
+	if _, err = exec.LookPath("yt-dlp"); err != nil {
+		err = fmt.Errorf("yt-dlp not found in PATH. Please install yt-dlp to use YouTube transcript functionality")
 		return
 	}
 
-	// Parse the XML transcript
-	doc := soup.HTMLParse(transcript)
-	// Extract the text content from the <text> tags
-	textTags := doc.FindAll("text")
-	var textBuilder strings.Builder
-	for _, textTag := range textTags {
-		// Extract the start and duration attributes
-		start := textTag.Attrs()["start"]
-		dur := textTag.Attrs()["dur"]
-		end := fmt.Sprintf("%f", parseFloat(start)+parseFloat(dur))
-		// Format the timestamps
-		startFormatted := formatTimestamp(parseFloat(start))
-		endFormatted := formatTimestamp(parseFloat(end))
-		text := strings.ReplaceAll(textTag.Text(), "&#39;", "'")
-		textBuilder.WriteString(fmt.Sprintf("[%s - %s] %s\n", startFormatted, endFormatted, text))
+	// Create a temporary directory for yt-dlp output (cross-platform)
+	tempDir := filepath.Join(os.TempDir(), "fabric-youtube-"+videoId)
+	if err = os.MkdirAll(tempDir, 0755); err != nil {
+		err = fmt.Errorf("failed to create temp directory: %v", err)
+		return
+	}
+	defer os.RemoveAll(tempDir)
+
+	// Use yt-dlp to get transcript
+	videoURL := "https://www.youtube.com/watch?v=" + videoId
+	outputPath := filepath.Join(tempDir, "%(title)s.%(ext)s")
+	lang_match := language
+	if len(language) > 2 {
+		lang_match = language[:2]
+	}
+	cmd := exec.Command("yt-dlp",
+		"--write-auto-subs",
+		"--sub-lang", lang_match,
+		"--skip-download",
+		"--sub-format", "vtt",
+		"--quiet",
+		"--no-warnings",
+		"-o", outputPath,
+		videoURL)
+
+	var stderr bytes.Buffer
+	cmd.Stderr = &stderr
+
+	if err = cmd.Run(); err != nil {
+		err = fmt.Errorf("yt-dlp failed: %v, stderr: %s", err, stderr.String())
+		return
+	}
+
+	// Find VTT files using cross-platform approach
+	vttFiles, err := o.findVTTFiles(tempDir, language)
+	if err != nil {
+		return "", err
+	}
+
+	return processVTTFileFunc(vttFiles[0])
+}
+
+func (o *YouTube) tryMethodYtDlp(videoId string, language string) (ret string, err error) {
+	return o.tryMethodYtDlpInternal(videoId, language, o.readAndCleanVTTFile)
+}
+
+func (o *YouTube) tryMethodYtDlpWithTimestamps(videoId string, language string) (ret string, err error) {
+	return o.tryMethodYtDlpInternal(videoId, language, o.readAndFormatVTTWithTimestamps)
+}
+
+func (o *YouTube) readAndCleanVTTFile(filename string) (ret string, err error) {
+	var content []byte
+	if content, err = os.ReadFile(filename); err != nil {
+		return
+	}
+
+	// Convert VTT to plain text
+	lines := strings.Split(string(content), "\n")
+	var textBuilder strings.Builder
+
+	for _, line := range lines {
+		line = strings.TrimSpace(line)
+		// Skip WEBVTT header, timestamps, and empty lines
+		if line == "" || line == "WEBVTT" || strings.Contains(line, "-->") ||
+			strings.HasPrefix(line, "NOTE") || strings.HasPrefix(line, "STYLE") ||
+			strings.HasPrefix(line, "Kind:") || strings.HasPrefix(line, "Language:") ||
+			isTimeStamp(line) {
+			continue
+		}
+		// Remove VTT formatting tags
+		line = removeVTTTags(line)
+		if line != "" {
+			textBuilder.WriteString(line)
+			textBuilder.WriteString(" ")
+		}
+	}
+
+	ret = strings.TrimSpace(textBuilder.String())
+	if ret == "" {
+		err = fmt.Errorf("no transcript content found in VTT file")
 	}
-	ret = textBuilder.String()
 	return
 }
 
-func parseFloat(s string) float64 {
-	f, _ := strconv.ParseFloat(s, 64)
-	return f
-}
-
-func formatTimestamp(seconds float64) string {
-	hours := int(seconds) / 3600
-	minutes := (int(seconds) % 3600) / 60
-	secs := int(seconds) % 60
-	return fmt.Sprintf("%02d:%02d:%02d", hours, minutes, secs)
-}
-
-func (o *YouTube) GrabTranscriptBase(videoId string, language string) (ret string, err error) {
-	if err = o.initService(); err != nil {
+func (o *YouTube) readAndFormatVTTWithTimestamps(filename string) (ret string, err error) {
+	var content []byte
+	if content, err = os.ReadFile(filename); err != nil {
 		return
 	}
 
-	watchUrl := "https://www.youtube.com/watch?v=" + videoId
-	var resp string
-	if resp, err = soup.Get(watchUrl); err != nil {
-		return
-	}
+	// Parse VTT and preserve timestamps
+	lines := strings.Split(string(content), "\n")
+	var textBuilder strings.Builder
+	var currentTimestamp string
 
-	doc := soup.HTMLParse(resp)
-	scriptTags := doc.FindAll("script")
-	for _, scriptTag := range scriptTags {
-		if strings.Contains(scriptTag.Text(), "captionTracks") {
-			regex := regexp.MustCompile(`"captionTracks":(\[.*?\])`)
-			match := regex.FindStringSubmatch(scriptTag.Text())
-			if len(match) > 1 {
-				var captionTracks []struct {
-					BaseURL string `json:"baseUrl"`
-				}
+	for _, line := range lines {
+		line = strings.TrimSpace(line)
 
-				if err = json.Unmarshal([]byte(match[1]), &captionTracks); err != nil {
-					return
-				}
+		// Skip WEBVTT header and empty lines
+		if line == "" || line == "WEBVTT" || strings.HasPrefix(line, "NOTE") ||
+			strings.HasPrefix(line, "STYLE") || strings.HasPrefix(line, "Kind:") ||
+			strings.HasPrefix(line, "Language:") {
+			continue
+		}
 
-				if len(captionTracks) > 0 {
-					transcriptURL := captionTracks[0].BaseURL
-					for _, captionTrack := range captionTracks {
-						parsedUrl, error := url.Parse(captionTrack.BaseURL)
-						if error != nil {
-							err = fmt.Errorf("error parsing caption track")
-						}
-						parsedUrlParams, _ := url.ParseQuery(parsedUrl.RawQuery)
-						if parsedUrlParams["lang"][0] == language {
-							transcriptURL = captionTrack.BaseURL
-						}
-					}
-					ret, err = soup.Get(transcriptURL)
-					return
-				}
+		// Check if this line is a timestamp
+		if strings.Contains(line, "-->") {
+			// Extract start time for this segment
+			parts := strings.Split(line, " --> ")
+			if len(parts) >= 1 {
+				currentTimestamp = formatVTTTimestamp(parts[0])
+			}
+			continue
+		}
+
+		// Skip numeric sequence identifiers
+		if isTimeStamp(line) && !strings.Contains(line, ":") {
+			continue
+		}
+
+		// This should be transcript text
+		if line != "" {
+			// Remove VTT formatting tags
+			cleanText := removeVTTTags(line)
+			if cleanText != "" && currentTimestamp != "" {
+				textBuilder.WriteString(fmt.Sprintf("[%s] %s\n", currentTimestamp, cleanText))
 			}
 		}
 	}
-	err = fmt.Errorf("transcript not found")
+
+	ret = strings.TrimSpace(textBuilder.String())
+	if ret == "" {
+		err = fmt.Errorf("no transcript content found in VTT file")
+	}
 	return
 }
 
+func formatVTTTimestamp(vttTime string) string {
+	// VTT timestamps are in format "00:00:01.234" - convert to "00:00:01"
+	parts := strings.Split(vttTime, ".")
+	if len(parts) > 0 {
+		return parts[0]
+	}
+	return vttTime
+}
+
+func isTimeStamp(s string) bool {
+	// Match timestamps like "00:00:01.234" or just numbers
+	timestampRegex := regexp.MustCompile(`^\d+$|^\d{2}:\d{2}:\d{2}`)
+	return timestampRegex.MatchString(s)
+}
+
+func removeVTTTags(s string) string {
+	// Remove VTT tags like <c.colorE5E5E5>, </c>, etc.
+	tagRegex := regexp.MustCompile(`<[^>]*>`)
+	return tagRegex.ReplaceAllString(s, "")
+}
+
 func (o *YouTube) GrabComments(videoId string) (ret []string, err error) {
 	if err = o.initService(); err != nil {
 		return
@@ -411,6 +490,41 @@ func (o *YouTube) normalizeFileName(name string) string {
 
 }
 
+// findVTTFiles searches for VTT files in a directory using cross-platform approach
+func (o *YouTube) findVTTFiles(dir, language string) ([]string, error) {
+	var vttFiles []string
+
+	// Walk through the directory to find VTT files
+	err := filepath.Walk(dir, func(path string, info os.FileInfo, err error) error {
+		if err != nil {
+			return err
+		}
+
+		if !info.IsDir() && strings.HasSuffix(strings.ToLower(path), ".vtt") {
+			vttFiles = append(vttFiles, path)
+		}
+		return nil
+	})
+
+	if err != nil {
+		return nil, fmt.Errorf("failed to walk directory: %v", err)
+	}
+
+	if len(vttFiles) == 0 {
+		return nil, fmt.Errorf("no VTT files found in directory")
+	}
+
+	// Prefer files with the specified language
+	for _, file := range vttFiles {
+		if strings.Contains(file, "."+language+".vtt") {
+			return []string{file}, nil
+		}
+	}
+
+	// Return the first VTT file found if no language-specific file exists
+	return []string{vttFiles[0]}, nil
+}
+
 type VideoMeta struct {
 	Id              string
 	Title           string

restapi/chat.go

@@ -3,14 +3,13 @@ package restapi
 import (
 	"encoding/json"
 	"fmt"
-	"io/ioutil"
 	"log"
 	"net/http"
 	"os"
 	"path/filepath"
 	"strings"
 
-	goopenai "github.com/sashabaranov/go-openai"
+	"github.com/danielmiessler/fabric/chat"
 
 	"github.com/danielmiessler/fabric/common"
 	"github.com/danielmiessler/fabric/core"
@@ -24,12 +23,13 @@ type ChatHandler struct {
 }
 
 type PromptRequest struct {
-	UserInput    string `json:"userInput"`
-	Vendor       string `json:"vendor"`
-	Model        string `json:"model"`
-	ContextName  string `json:"contextName"`
-	PatternName  string `json:"patternName"`
-	StrategyName string `json:"strategyName"` // Optional strategy name
+	UserInput    string            `json:"userInput"`
+	Vendor       string            `json:"vendor"`
+	Model        string            `json:"model"`
+	ContextName  string            `json:"contextName"`
+	PatternName  string            `json:"patternName"`
+	StrategyName string            `json:"strategyName"`        // Optional strategy name
+	Variables    map[string]string `json:"variables,omitempty"` // Pattern variables
 }
 
 type ChatRequest struct {
@@ -94,7 +94,7 @@ func (h *ChatHandler) HandleChat(c *gin.Context) {
 				// Load and prepend strategy prompt if strategyName is set
 				if p.StrategyName != "" {
 					strategyFile := filepath.Join(os.Getenv("HOME"), ".config", "fabric", "strategies", p.StrategyName+".json")
-					data, err := ioutil.ReadFile(strategyFile)
+					data, err := os.ReadFile(strategyFile)
 					if err == nil {
 						var s struct {
 							Prompt string `json:"prompt"`
@@ -114,13 +114,14 @@ func (h *ChatHandler) HandleChat(c *gin.Context) {
 
 				// Pass the language received in the initial request to the common.ChatRequest
 				chatReq := &common.ChatRequest{
-					Message: &goopenai.ChatCompletionMessage{
+					Message: &chat.ChatCompletionMessage{
 						Role:    "user",
 						Content: p.UserInput,
 					},
-					PatternName: p.PatternName,
-					ContextName: p.ContextName,
-					Language:    request.Language, // Pass the language field
+					PatternName:      p.PatternName,
+					ContextName:      p.ContextName,
+					PatternVariables: p.Variables,      // Pass pattern variables
+					Language:         request.Language, // Pass the language field
 				}
 
 				opts := &common.ChatOptions{

restapi/docs/API_VARIABLES_EXAMPLE.md

@@ -0,0 +1,105 @@
+# REST API Pattern Variables Example
+
+This example demonstrates how to use pattern variables in REST API calls to the `/chat` endpoint.
+
+## Example: Using the `translate` pattern with variables
+
+### Request
+
+```json
+{
+  "prompts": [
+    {
+      "userInput": "Hello my name is Kayvan",
+      "patternName": "translate",
+      "model": "gpt-4o",
+      "vendor": "openai",
+      "contextName": "",
+      "strategyName": "",
+      "variables": {
+        "lang_code": "fr"
+      }
+    }
+  ],
+  "language": "en",
+  "temperature": 0.7,
+  "topP": 0.9,
+  "frequencyPenalty": 0.0,
+  "presencePenalty": 0.0
+}
+```
+
+### Pattern Content
+
+The `translate` pattern contains:
+
+```markdown
+You are an expert translator... translate them as accurately and perfectly as possible into the language specified by its language code {{lang_code}}...
+
+...
+
+- Translate the document as accurately as possible keeping a 1:1 copy of the original text translated to {{lang_code}}.
+
+{{input}}
+```
+
+### How it works
+
+1. The pattern is loaded from `patterns/translate/system.md`
+2. The `{{lang_code}}` variable is replaced with `"fr"` from the variables map
+3. The `{{input}}` placeholder is replaced with `"Hello my name is Kayvan"`
+4. The resulting processed pattern is sent to the AI model
+
+### Expected Result
+
+The AI would receive a prompt asking it to translate "Hello my name is Kayvan" to French (fr), and would respond with something like "Bonjour, je m'appelle Kayvan".
+
+## Testing with curl
+
+```bash
+curl -X POST http://localhost:8080/api/chat \
+  -H "Content-Type: application/json" \
+  -d '{
+    "prompts": [
+      {
+        "userInput": "Hello my name is Kayvan",
+        "patternName": "translate",
+        "model": "gpt-4o",
+        "vendor": "openai",
+        "variables": {
+          "lang_code": "fr"
+        }
+      }
+    ],
+    "temperature": 0.7
+  }'
+```
+
+## Multiple Variables Example
+
+For patterns that use multiple variables:
+
+```json
+{
+  "prompts": [
+    {
+      "userInput": "Analyze this business model",
+      "patternName": "custom_analysis",
+      "model": "gpt-4o",
+      "variables": {
+        "role": "expert consultant",
+        "experience": "15",
+        "focus_areas": "revenue, scalability, market fit",
+        "output_format": "bullet points"
+      }
+    }
+  ]
+}
+```
+
+## Implementation Details
+
+- Variables are passed in the `variables` field as a key-value map
+- Variables are processed using Go's template system
+- The `{{input}}` variable is automatically handled and should not be included in the variables map
+- Variables support the same features as CLI variables (plugins, extensions, etc.)

restapi/ollama.go

@@ -103,7 +103,6 @@ func ServeOllama(registry *core.PluginRegistry, address string, version string)
 	r.GET("/api/tags", typeConversion.ollamaTags)
 	r.GET("/api/version", func(c *gin.Context) {
 		c.Data(200, "application/json", []byte(fmt.Sprintf("{\"%s\"}", version)))
-		return
 	})
 	r.POST("/api/chat", typeConversion.ollamaChat)
 
@@ -262,15 +261,10 @@ func (f APIConvert) ollamaChat(c *gin.Context) {
 			c.JSON(http.StatusInternalServerError, gin.H{"error": err})
 			return
 		}
-		for _, bytein := range marshalled {
-			res = append(res, bytein)
-		}
-		for _, bytebreak := range []byte("\n") {
-			res = append(res, bytebreak)
-		}
+		res = append(res, marshalled...)
+		res = append(res, '\n')
 	}
 	c.Data(200, "application/json", res)
 
 	//c.JSON(200, forwardedResponse)
-	return
 }

restapi/patterns.go

@@ -15,20 +15,70 @@ type PatternsHandler struct {
 
 // NewPatternsHandler creates a new PatternsHandler
 func NewPatternsHandler(r *gin.Engine, patterns *fsdb.PatternsEntity) (ret *PatternsHandler) {
-	ret = &PatternsHandler{
-		StorageHandler: NewStorageHandler(r, "patterns", patterns), patterns: patterns}
+	// Create a storage handler but don't register any routes yet
+	storageHandler := &StorageHandler[fsdb.Pattern]{storage: patterns}
+	ret = &PatternsHandler{StorageHandler: storageHandler, patterns: patterns}
 
-	// TODO: Add custom, replacement routes here
-	//r.GET("/patterns/:name", ret.Get)
+	// Register routes manually - use custom Get for patterns, others from StorageHandler
+	r.GET("/patterns/:name", ret.Get)                       // Custom method with variables support
+	r.GET("/patterns/names", ret.GetNames)                  // From StorageHandler
+	r.DELETE("/patterns/:name", ret.Delete)                 // From StorageHandler
+	r.GET("/patterns/exists/:name", ret.Exists)             // From StorageHandler
+	r.PUT("/patterns/rename/:oldName/:newName", ret.Rename) // From StorageHandler
+	r.POST("/patterns/:name", ret.Save)                     // From StorageHandler
+	// Add POST route for patterns with variables in request body
+	r.POST("/patterns/:name/apply", ret.ApplyPattern)
 	return
 }
 
-// Get handles the GET /patterns/:name route
+// Get handles the GET /patterns/:name route - returns raw pattern without variable processing
 func (h *PatternsHandler) Get(c *gin.Context) {
 	name := c.Param("name")
-	variables := make(map[string]string) // Assuming variables are passed somehow
-	input := ""                          // Assuming input is passed somehow
-	pattern, err := h.patterns.GetApplyVariables(name, variables, input)
+
+	// Get the raw pattern content without any variable processing
+	content, err := h.patterns.Load(name + "/" + h.patterns.SystemPatternFile)
+	if err != nil {
+		c.JSON(http.StatusInternalServerError, err.Error())
+		return
+	}
+
+	// Return raw pattern in the same format as the processed patterns
+	pattern := &fsdb.Pattern{
+		Name:        name,
+		Description: "",
+		Pattern:     string(content),
+	}
+	c.JSON(http.StatusOK, pattern)
+}
+
+// PatternApplyRequest represents the request body for applying a pattern
+type PatternApplyRequest struct {
+	Input     string            `json:"input"`
+	Variables map[string]string `json:"variables,omitempty"`
+}
+
+// ApplyPattern handles the POST /patterns/:name/apply route
+func (h *PatternsHandler) ApplyPattern(c *gin.Context) {
+	name := c.Param("name")
+
+	var request PatternApplyRequest
+	if err := c.ShouldBindJSON(&request); err != nil {
+		c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
+		return
+	}
+
+	// Merge query parameters with request body variables (body takes precedence)
+	variables := make(map[string]string)
+	for key, values := range c.Request.URL.Query() {
+		if len(values) > 0 {
+			variables[key] = values[0]
+		}
+	}
+	for key, value := range request.Variables {
+		variables[key] = value
+	}
+
+	pattern, err := h.patterns.GetApplyVariables(name, variables, request.Input)
 	if err != nil {
 		c.JSON(http.StatusInternalServerError, err.Error())
 		return

restapi/serve.go

@@ -26,6 +26,7 @@ func Serve(registry *core.PluginRegistry, address string, apiKey string) (err er
 	NewContextsHandler(r, fabricDb.Contexts)
 	NewSessionsHandler(r, fabricDb.Sessions)
 	NewChatHandler(r, registry, fabricDb)
+	NewYouTubeHandler(r, registry)
 	NewConfigHandler(r, fabricDb)
 	NewModelsHandler(r, registry.VendorManager)
 	NewStrategiesHandler(r)

restapi/strategies.go

@@ -2,7 +2,6 @@ package restapi
 
 import (
 	"encoding/json"
-	"io/ioutil"
 	"net/http"
 	"os"
 	"path/filepath"
@@ -23,7 +22,7 @@ func NewStrategiesHandler(r *gin.Engine) {
 	r.GET("/strategies", func(c *gin.Context) {
 		strategiesDir := filepath.Join(os.Getenv("HOME"), ".config", "fabric", "strategies")
 
-		files, err := ioutil.ReadDir(strategiesDir)
+		files, err := os.ReadDir(strategiesDir)
 		if err != nil {
 			c.JSON(http.StatusInternalServerError, gin.H{"error": "Failed to read strategies directory"})
 			return
@@ -37,7 +36,7 @@ func NewStrategiesHandler(r *gin.Engine) {
 			}
 
 			fullPath := filepath.Join(strategiesDir, file.Name())
-			data, err := ioutil.ReadFile(fullPath)
+			data, err := os.ReadFile(fullPath)
 			if err != nil {
 				continue
 			}

restapi/youtube.go

@@ -0,0 +1,70 @@
+package restapi
+
+import (
+	"net/http"
+
+	"github.com/danielmiessler/fabric/core"
+	"github.com/danielmiessler/fabric/plugins/tools/youtube"
+	"github.com/gin-gonic/gin"
+)
+
+type YouTubeHandler struct {
+	yt *youtube.YouTube
+}
+
+type YouTubeRequest struct {
+	URL        string `json:"url"`
+	Language   string `json:"language"`
+	Timestamps bool   `json:"timestamps"`
+}
+
+type YouTubeResponse struct {
+	Transcript string `json:"transcript"`
+	Title      string `json:"title"`
+}
+
+func NewYouTubeHandler(r *gin.Engine, registry *core.PluginRegistry) *YouTubeHandler {
+	handler := &YouTubeHandler{yt: registry.YouTube}
+	r.POST("/youtube/transcript", handler.Transcript)
+	return handler
+}
+
+func (h *YouTubeHandler) Transcript(c *gin.Context) {
+	var req YouTubeRequest
+	if err := c.BindJSON(&req); err != nil {
+		c.JSON(http.StatusBadRequest, gin.H{"error": "invalid request"})
+		return
+	}
+	if req.URL == "" {
+		c.JSON(http.StatusBadRequest, gin.H{"error": "url is required"})
+		return
+	}
+	language := req.Language
+	if language == "" {
+		language = "en"
+	}
+
+	var videoID, playlistID string
+	var err error
+	if videoID, playlistID, err = h.yt.GetVideoOrPlaylistId(req.URL); err != nil {
+		c.JSON(http.StatusBadRequest, gin.H{"error": err.Error()})
+		return
+	}
+	if videoID == "" && playlistID != "" {
+		c.JSON(http.StatusBadRequest, gin.H{"error": "URL is a playlist, not a video"})
+		return
+	}
+
+	var transcript string
+	if req.Timestamps {
+		transcript, err = h.yt.GrabTranscriptWithTimestamps(videoID, language)
+	} else {
+		transcript, err = h.yt.GrabTranscript(videoID, language)
+	}
+	if err != nil {
+		c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
+		return
+	}
+
+	c.JSON(http.StatusOK, YouTubeResponse{Transcript: transcript, Title: videoID})
+}

stitches/rate_ai_result/rate_ai_result.txt

@@ -1 +0,0 @@
-(echo "beginning of content input" ; f -u https://danielmiessler.com/p/framing-is-everything ; echo "end of content input"; echo "beginning of AI instructions (prompt)"; cat ~/.config/fabric/patterns/extract_insights/system.md; echo "endof AI instructions (prompt)" ; echo "beginning of AI output" ; f -u https://danielmiessler.com/p/framing-is-everything | f -p extract_insights -m gpt-3.5-turbo; echo "end of AI output. Now you should have all three." ) | f -rp rate_ai_result -m o1-preview-2024-09-12

stitches/rate_ai_result/readme.md

@@ -1,60 +0,0 @@
-# Rate AI Result
-
-This is an example of a Fabric Stitch, which is a chained Fabric command that pipes Fabric results into each other to achieve a result. So it's multiple Patterns…*stitched* together.
-
-## Problem
-
-The problem we're trying to solve with this Stitch is not being able to tell how smart given AI models are. I want to be able to rate their output vs. the output from a different model with the same instructions.
-
-## Solution
-
-What `rate_ai_result` does is run a result using AI 1, and then rate it with AI 2.
-
-## Functionality
-
-`rate_ai_result` accomplishes that like so:
-
-1. Get the input that will be operated on by an AI.
-2. Get the instruction/pattern/prompt that will be used by the AI.
-3. Get the result of the instructions running against the AI.
-4. Combine all three of those together as the input to another Fabric call.
-4. Send that combined input to the most advanced model you have available to assess the quality of the AI result.
-
-```
-(echo "beginning of content input" ; f -u https://danielmiessler.com/p/framing-is-everything ; echo "end ofcontent input"; echo "beginning of AI instructions (prompt)"; cat ~/.config/fabric/patterns/extract_insights/system.md; echo "end of AI instructions (prompt)" ; echo "beginning of AI output" ; f -u https://danielmiessler.com/p/framing-is-everything | f -p extract_insights -m gpt-3.5-turbo ; echo "end of AI output. Now you should have all three." ) | f -rp rate_ai_result -m o1-preview-2024-09-12
-```
-In this case we're taking:
-
-* A blog post as the input
-* Getting the content of the extract_insights pattern
-* Capturing the output of extract_insights on the blog post using `gpt-3.5-turbo`
-* Sending all of that to `o1-preview` using the `rate_ai_result` prompt
-
-NOTE: `rate_ai_result` is both a Pattern name and the name of this Stitch.
-
-## Output 
-
-The `rate_ai_result` Pattern is designed to judge the output of another AI on a human sophistication scale that roughly maps to educational and world-state achievement, with the assumption that higher stages require higher cognitive ability as well. These are:
-
-- Superhuman
-- Best humans in the world
-- Ph.D
-- Masters
-- Bachelors
-- High School
-- Partially Educated
-- Uneducated
-
-## How to run it
-
-To run it, just execute the code in the `rate_ai_result` file in this repository. And adjust the components as desired to change the input, the AI you're testing, and the AI you're using to judge.
-
-### Blog Post
-
-Here's a full blog post describing in even more detail.
-
-[Using the Smartest AI to Rate Other AI](https://danielmiessler.com/p/using-the-smartest-ai-to-rate-other-ai)
-
-#### Credit
-
-Created by Daniel Miessler on November 7th, 2024.

version.go

@@ -1,3 +1,3 @@
 package main
 
-var version = "v1.4.183"
+var version = "v1.4.222"

web/.browserslistrc

@@ -0,0 +1,6 @@
+last 2 versions
+not dead
+chrome >= 89
+firefox >= 89
+safari >= 15
+edge >= 89

web/README.md

@@ -1,25 +1,83 @@
 # The Fabric Web App
-[Installing](#Installing)|[Todos](#Todos)|[Collaborators](#Collaborators)
 
-This is a web app for Fabric. It was built using [Svelte](https://svelte.dev/), [SkeletonUI](https://skeleton.dev/), and [Mdsvex](https://mdsvex.pngwn.io/). 
+- [The Fabric Web App](#the-fabric-web-app)
+  - [Installing](#installing)
+    - [From Source](#from-source)
+      - [TL;DR: Convenience Scripts](#tldr-convenience-scripts)
+  - [Tips](#tips)
+  - [Obsidian](#obsidian)
 
-The goal of this app is to not only provide a user interface for Fabric, but also a out-of-the-box website for those who want to get started with web development, blogging, or to just have a web interface for fabric. You can use this app as a GUI interface for Fabric, a ready to go blog-site, or a website template for your own projects. 
+This is a web app for Fabric. It was built using [Svelte][svelte], [SkeletonUI][skeleton], and [Mdsvex][mdsvex].
 
-![Preview](/fabric-png.png)
+The goal of this app is to not only provide a user interface for Fabric, but also an out-of-the-box website for those who want to get started with web development, blogging, or to just have a web interface for fabric. You can use this app as a GUI interface for Fabric, a ready to go blog-site, or a website template for your own projects.
+
+![Preview](./static/preview.png)
 
 ## Installing
 
+There are a few days to install and run the Web UI.
+
+### From Source
+
+#### TL;DR: Convenience Scripts
+
+To install the Web UI using `npm`, from the top-level directory:
+
+```bash
+./web/scripts/npm-install.sh
+```
+
+To use pnpm (preferred and recommended for a huge speed improvement):
+
+```bash
+./web/scripts/pnpm-install.sh
+```
+
 The app can be run by navigating to the `web` directory and using `npm install`, `pnpm install`, or your preferred package manager. Then simply run `npm run dev`, `pnpm run dev`, or your equivalent command to start the app. *You will need to run fabric in a separate terminal with the `fabric --serve` command.*
 
+Using npm:
+
+```bash
+# Install the GUI and its dependencies
+npm install
+# Install PDF-to-Markdown components in this order
+npm install -D patch-package
+npm install -D pdfjs-dist
+npm install -D github:jzillmann/pdf-to-markdown#modularize
+
+npx svelte-kit sync
+
+# Now, with "fabric --serve" running already, you can run the GUI
+npm run dev
+```
+
+Using pnpm:
+
+```bash
+# Install the GUI and its dependencies
+pnpm install
+# Install PDF-to-Markdown components in this order
+pnpm install -D patch-package
+pnpm install -D pdfjs-dist
+pnpm install -D github:jzillmann/pdf-to-markdown#modularize
+
+pnpm exec svelte-kit sync
+
+# Now, with "fabric --serve" running already, you can run the GUI
+pnpm run dev
+```
+
 ## Tips
 
 When creating new posts make sure to include a date, description, tags, and aliases. Only a date is needed to display a note.
 
-You can include images, tags to other articles, code blocks, and more all within your markdown files. 
-
-### If you choose to use Obsidian along side ths app
-
-You can design and order your vault however you like, though a `posts` folder should be kept in your vault to house any articles you'd like to post. 
+You can include images, tags to other articles, code blocks, and more all within your markdown files.
 
+## Obsidian
 
+If you choose to use Obsidian alongside this app,
+you can design and order your vault however you like, though a `posts` folder should be kept in your vault to house any articles you'd like to post.
 
+[svelte]: https://svelte.dev/
+[skeleton]: https://skeleton.dev/
+[mdsvex]: https://mdsvex.pngwn.io/