chore(release): Update version to v1.4.306

Documentation and Pattern Updates

.github/pull_request_template.md

@@ -1,9 +1,12 @@
 ## What this Pull Request (PR) does
+
 Please briefly describe what this PR does.
 
 ## Related issues
+
 Please reference any open issues this PR relates to in here.
 If it closes an issue, type `closes #[ISSUE_NUMBER]`.
 
 ## Screenshots
+
 Provide any screenshots you may find relevant to facilitate us understanding your PR.

.github/workflows/ci.yml

@@ -20,13 +20,13 @@ jobs:
       contents: read
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
 
       - name: Install Nix
         uses: DeterminateSystems/nix-installer-action@main
 
       - name: Set up Go
-        uses: actions/setup-go@v4
+        uses: actions/setup-go@v5
         with:
           go-version-file: ./go.mod
 

.github/workflows/patterns.yaml

@@ -11,22 +11,27 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           fetch-depth: 0
 
       - name: Verify Changes in Patterns Folder
+        id: check-changes
         run: |
           git fetch origin
           if git diff --quiet HEAD~1 -- data/patterns; then
             echo "No changes detected in patterns folder."
-            exit 1
+            echo "changes=false" >> $GITHUB_OUTPUT
+          else
+            echo "Changes detected in patterns folder."
+            echo "changes=true" >> $GITHUB_OUTPUT
           fi
-
       - name: Zip the Patterns Folder
+        if: steps.check-changes.outputs.changes == 'true'
         run: zip -r patterns.zip data/patterns/
 
       - name: Upload Patterns Artifact
+        if: steps.check-changes.outputs.changes == 'true'
         uses: actions/upload-artifact@v4
         with:
           name: patterns

.github/workflows/release.yml

@@ -15,149 +15,43 @@ jobs:
       contents: read
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           fetch-depth: 0
 
       - name: Set up Go
-        uses: actions/setup-go@v4
+        uses: actions/setup-go@v5
         with:
           go-version-file: ./go.mod
 
       - name: Run tests
         run: go test -v ./...
 
-  get_version:
-    name: Get version
-    runs-on: ubuntu-latest
-    outputs:
-      latest_tag: ${{ steps.get_version.outputs.latest_tag }}
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-
-      - name: Get version from source
-        id: get_version
-        shell: bash
-        run: |
-          if [ ! -f "nix/pkgs/fabric/version.nix" ]; then
-            echo "Error: version.nix file not found"
-            exit 1
-          fi
-          version=$(cat nix/pkgs/fabric/version.nix | tr -d '"' | tr -cd '0-9.')
-          if [ -z "$version" ]; then
-            echo "Error: version is empty"
-            exit 1
-          fi
-          if ! echo "$version" | grep -E '^[0-9]+\.[0-9]+\.[0-9]+' > /dev/null; then
-            echo "Error: Invalid version format: $version"
-            exit 1
-          fi
-          echo "latest_tag=v$version" >> $GITHUB_OUTPUT
-
   build:
-    name: Build binaries for Windows, macOS, and Linux
-    needs: [test, get_version]
-    runs-on: ${{ matrix.os }}
-    permissions:
-      contents: write
-    strategy:
-      matrix:
-        os: [ubuntu-latest, macos-latest, windows-latest]
-        arch: [amd64, arm64]
-        exclude:
-          - os: windows-latest
-            arch: arm64
-
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-
-      - name: Set up Go
-        uses: actions/setup-go@v4
-        with:
-          go-version-file: ./go.mod
-
-      - name: Build binary on Linux and macOS
-        if: matrix.os != 'windows-latest'
-        env:
-          GOOS: ${{ matrix.os == 'ubuntu-latest' && 'linux' || 'darwin' }}
-          GOARCH: ${{ matrix.arch }}
-        run: |
-          OS_NAME="${{ matrix.os == 'ubuntu-latest' && 'linux' || 'darwin' }}"
-          go build -o fabric-${OS_NAME}-${{ matrix.arch }} ./cmd/fabric
-
-      - name: Build binary on Windows
-        if: matrix.os == 'windows-latest'
-        env:
-          GOOS: windows
-          GOARCH: ${{ matrix.arch }}
-        run: |
-          go build -o fabric-windows-${{ matrix.arch }}.exe ./cmd/fabric
-
-      - name: Upload build artifact
-        if: matrix.os != 'windows-latest'
-        uses: actions/upload-artifact@v4
-        with:
-          name: fabric-${{ matrix.os == 'ubuntu-latest' && 'linux' || 'darwin' }}-${{ matrix.arch }}
-          path: fabric-${{ matrix.os == 'ubuntu-latest' && 'linux' || 'darwin' }}-${{ matrix.arch }}
-
-      - name: Upload build artifact
-        if: matrix.os == 'windows-latest'
-        uses: actions/upload-artifact@v4
-        with:
-          name: fabric-windows-${{ matrix.arch }}.exe
-          path: fabric-windows-${{ matrix.arch }}.exe
-
-      - name: Create release if it doesn't exist
-        shell: bash
-        env:
-          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        run: |
-          if ! gh release view ${{ needs.get_version.outputs.latest_tag }} >/dev/null 2>&1; then
-            gh release create ${{ needs.get_version.outputs.latest_tag }} --title "Release ${{ needs.get_version.outputs.latest_tag }}" --notes "Automated release for ${{ needs.get_version.outputs.latest_tag }}"
-          else
-            echo "Release ${{ needs.get_version.outputs.latest_tag }} already exists."
-          fi
-
-      - name: Upload release artifact
-        if: matrix.os == 'windows-latest'
-        env:
-          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        run: |
-          gh release upload ${{ needs.get_version.outputs.latest_tag }} fabric-windows-${{ matrix.arch }}.exe
-
-      - name: Upload release artifact
-        if: matrix.os != 'windows-latest'
-        env:
-          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        run: |
-          OS_NAME="${{ matrix.os == 'ubuntu-latest' && 'linux' || 'darwin' }}"
-          gh release upload ${{ needs.get_version.outputs.latest_tag }} fabric-${OS_NAME}-${{ matrix.arch }}
-
-  update_release_notes:
-    needs: [build, get_version]
+    # only run in main upstream repo
+    if: ${{ github.repository_owner == 'danielmiessler' }}
+    name: Build & Release with Goreleaser
+    needs: [test]
     runs-on: ubuntu-latest
     permissions:
       contents: write
     steps:
       - name: Checkout code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           fetch-depth: 0
-
       - name: Set up Go
-        uses: actions/setup-go@v4
+        uses: actions/setup-go@v5
         with:
           go-version-file: ./go.mod
-
-      - name: Update release description
+      - name: Run GoReleaser
+        uses: goreleaser/goreleaser-action@v6
+        with:
+          distribution: goreleaser
+          args: release --clean
         env:
-          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        run: |
-          go run ./cmd/generate_changelog --sync-db
-          go run ./cmd/generate_changelog --release ${{ needs.get_version.outputs.latest_tag }}
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+      - name: Update Release Description
+        run: go run ./cmd/generate_changelog --release ${{ github.event.client_payload.tag || github.ref_name }}
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

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

@@ -6,7 +6,6 @@ on:
       - main # Monitor the main branch
     paths-ignore:
       - "data/patterns/**"
-      - "**/*.md"
       - "data/strategies/**"
       - "cmd/generate_changelog/*.db"
       - "cmd/generate_changelog/incoming/*.txt"
@@ -22,12 +21,13 @@ concurrency:
 
 jobs:
   update-version:
-    if: github.event_name == 'push' && github.ref == 'refs/heads/main'
+    if: >
+      ${{ github.repository_owner == 'danielmiessler' }} &&
+      github.event_name == 'push' && github.ref == 'refs/heads/main'
     runs-on: ubuntu-latest
-
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v5
         with:
           fetch-depth: 0
 
@@ -49,12 +49,13 @@ jobs:
         run: |
           latest_tag=$(git tag --sort=-creatordate | head -n 1)
           echo "Latest tag is: $latest_tag"
+          echo "tag=$latest_tag" >> $GITHUB_OUTPUT
           echo "tag=$latest_tag" >> $GITHUB_ENV  # Save the latest tag to environment file
 
       - name: Increment patch version
         id: increment_version
         run: |
-          latest_tag=${{ env.tag }}
+          latest_tag=${{ steps.get_latest_tag.outputs.tag }}
           major=$(echo "$latest_tag" | cut -d. -f1 | sed 's/v//')
           minor=$(echo "$latest_tag" | cut -d. -f2)
           patch=$(echo "$latest_tag" | cut -d. -f3)
@@ -62,19 +63,21 @@ jobs:
           new_version="${major}.${minor}.${new_patch}"
           new_tag="v${new_version}"
           echo "New version is: $new_version"
+          echo "new_version=$new_version" >> $GITHUB_OUTPUT
           echo "new_version=$new_version" >> $GITHUB_ENV  # Save the new version to environment file
           echo "New tag is: $new_tag"
+          echo "new_tag=$new_tag" >> $GITHUB_OUTPUT
           echo "new_tag=$new_tag" >> $GITHUB_ENV  # Save the new tag to environment file
 
       - name: Update version.go file
         run: |
           echo "package main" > cmd/fabric/version.go
           echo "" >> cmd/fabric/version.go
-          echo "var version = \"${{ env.new_tag }}\"" >> cmd/fabric/version.go
+          echo "var version = \"${{ steps.increment_version.outputs.new_tag }}\"" >> cmd/fabric/version.go
 
       - name: Update version.nix file
         run: |
-          echo "\"${{ env.new_version }}\"" > nix/pkgs/fabric/version.nix
+          echo "\"${{ steps.increment_version.outputs.new_version }}\"" > nix/pkgs/fabric/version.nix
 
       - name: Format source code
         run: |
@@ -88,7 +91,7 @@ jobs:
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run: |
-          go run ./cmd/generate_changelog --process-prs ${{ env.new_tag }}
+          go run ./cmd/generate_changelog --process-prs ${{ steps.increment_version.outputs.new_tag }}
           go run ./cmd/generate_changelog --sync-db
       - name: Commit changes
         run: |
@@ -101,7 +104,7 @@ jobs:
           # and removing the incoming/ directory.
 
           if ! git diff --staged --quiet; then
-            git commit -m "chore(release): Update version to ${{ env.new_tag }}"
+            git commit -m "chore(release): Update version to ${{ steps.increment_version.outputs.new_tag }}"
           else
             echo "No changes to commit."
           fi
@@ -114,10 +117,10 @@ jobs:
 
       - name: Create a new tag
         env:
-          GITHUB_TOKEN: ${{ secrets.TAG_PAT }}
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run: |
-          git tag ${{ env.new_tag }}
-          git push origin ${{ env.new_tag }}  # Push the new tag
+          git tag ${{ steps.increment_version.outputs.new_tag }}
+          git push origin ${{ steps.increment_version.outputs.new_tag }}  # Push the new tag
 
       - name: Dispatch event to trigger release workflow
         env:
@@ -127,4 +130,4 @@ jobs:
             -H "Authorization: token $GITHUB_TOKEN" \
             -H "Accept: application/vnd.github.v3+json" \
             https://api.github.com/repos/${{ github.repository }}/dispatches \
-            -d '{"event_type": "tag_created", "client_payload": {"tag": "${{ env.new_tag }}"}}'
+            -d '{"event_type": "tag_created", "client_payload": {"tag": "${{ steps.increment_version.outputs.new_tag }}"}}'

.goreleaser.yaml

@@ -0,0 +1,36 @@
+# Read the documentation at https://goreleaser.com
+
+version: 2
+
+project_name: fabric
+before:
+  hooks:
+    # You may remove this if you don't use go modules.
+    - go mod tidy
+    # you may remove this if you don't need go generate
+    # - go generate ./...
+
+builds:
+  - env:
+      - CGO_ENABLED=0
+    goos:
+      - linux
+      - windows
+      - darwin
+    main: ./cmd/fabric
+    binary: fabric
+
+archives:
+  - formats: [tar.gz]
+    # this name template makes the OS and Arch compatible with the results of `uname`.
+    name_template: >-
+      {{ .ProjectName }}_
+      {{- title .Os }}_
+      {{- if eq .Arch "amd64" }}x86_64
+      {{- else if eq .Arch "386" }}i386
+      {{- else }}{{ .Arch }}{{ end }}
+      {{- if .Arm }}v{{ .Arm }}{{ end }}
+    # use zip for windows archives
+    format_overrides:
+      - goos: windows
+        formats: [zip]

.vscode/settings.json

@@ -4,6 +4,7 @@
 		"addextension",
 		"adduser",
 		"AIML",
+		"Anki",
 		"anthropics",
 		"Aoede",
 		"atotto",
@@ -12,6 +13,7 @@
 		"Behrens",
 		"blindspots",
 		"Bombal",
+		"Buildx",
 		"Callirhoe",
 		"Callirrhoe",
 		"Cerebras",
@@ -24,15 +26,19 @@
 		"danielmiessler",
 		"davidanson",
 		"Debugf",
+		"debuglog",
 		"dedup",
 		"deepseek",
 		"Despina",
 		"direnv",
+		"DMARC",
+		"DOCKERHUB",
 		"dryrun",
 		"dsrp",
 		"editability",
 		"Eisler",
 		"elif",
+		"Elister",
 		"envrc",
 		"Erinome",
 		"Errorf",
@@ -53,11 +59,13 @@
 		"godotenv",
 		"gofmt",
 		"goimports",
+		"golint",
 		"gomod",
 		"gonic",
 		"goopenai",
 		"GOPATH",
 		"gopkg",
+		"Goreleaser",
 		"GOROOT",
 		"Graphviz",
 		"grokai",
@@ -69,10 +77,12 @@
 		"Hormozi's",
 		"horts",
 		"HTMLURL",
+		"imagetools",
 		"jaredmontoya",
 		"jessevdk",
 		"Jina",
 		"joho",
+		"kballard",
 		"Keploy",
 		"Kore",
 		"ksylvan",
@@ -96,12 +106,17 @@
 		"mbed",
 		"metacharacters",
 		"Miessler",
+		"modeline",
+		"modelines",
+		"mpga",
 		"nometa",
 		"numpy",
 		"ollama",
 		"ollamaapi",
+		"Omri",
 		"openaiapi",
 		"opencode",
+		"opencontainers",
 		"openrouter",
 		"Orus",
 		"osascript",
@@ -127,6 +142,9 @@
 		"seaborn",
 		"semgrep",
 		"sess",
+		"sgaunet",
+		"shellquote",
+		"SSEHTTP",
 		"storer",
 		"Streamlit",
 		"stretchr",
@@ -147,13 +165,16 @@
 		"videoid",
 		"webp",
 		"WEBVTT",
+		"winget",
 		"wipecontext",
 		"wipesession",
+		"wireframes",
 		"Worktree",
 		"writeups",
 		"xclip",
 		"yourpatternname",
-		"youtu"
+		"youtu",
+		"YTDLP"
 	],
 	"cSpell.ignorePaths": ["go.mod", ".gitignore", "CHANGELOG.md"],
 	"markdownlint.config": {

CHANGELOG.md

@@ -1,5 +1,238 @@
 # Changelog
 
+## v1.4.306 (2025-09-01)
+
+### PR [#1742](https://github.com/danielmiessler/Fabric/pull/1742) by [ksylvan](https://github.com/ksylvan): Documentation and Pattern Updates
+
+- Add winget installation method for Windows users
+- Include Docker Hub and GHCR image references with docker run examples
+- Remove deprecated PowerShell download link and unused show_fabric_options_markmap pattern
+- Update suggest_pattern with new AI patterns
+- Add personal development patterns for storytelling
+
+## v1.4.305 (2025-08-31)
+
+### PR [#1741](https://github.com/danielmiessler/Fabric/pull/1741) by [ksylvan](https://github.com/ksylvan): CI: Fix Release Description Update
+
+- Fix: update release workflow to support manual dispatch with custom tag
+- Support custom tag from client payload in workflow
+- Fallback to github.ref_name when no custom tag provided
+- Enable manual release triggers with specified tag parameter
+
+## v1.4.304 (2025-08-31)
+
+### PR [#1740](https://github.com/danielmiessler/Fabric/pull/1740) by [ksylvan](https://github.com/ksylvan): Restore our custom Changelog Updates in GitHub Actions
+
+- Add changelog generation step to GitHub release workflow
+- Create updateReleaseForRepo helper method for release updates
+- Add fork detection logic in UpdateReleaseDescription method
+- Implement upstream repository release update for forks
+- Enhance error handling with detailed repository context
+
+## v1.4.303 (2025-08-28)
+
+### PR [#1736](https://github.com/danielmiessler/Fabric/pull/1736) by [tonymet](https://github.com/tonymet): Winget Publishing and GoReleaser
+
+- Added GoReleaser support for improved package distribution
+- Winget and Docker publishing moved to ksylvan/fabric-packager GitHub repo
+- Hardened release pipeline by gating workflows to upstream owner only
+- Migrated from custom tokens to built-in GITHUB_TOKEN for enhanced security
+- Removed docker-publish-on-tag workflow to reduce duplication and complexity
+- Added ARM binary release support with updated documentation
+
+## v1.4.302 (2025-08-28)
+
+### PR [#1737](https://github.com/danielmiessler/Fabric/pull/1737) by [ksylvan](https://github.com/ksylvan) and [OmriH-Elister](https://github.com/OmriH-Elister): Add New Psychological Analysis Patterns + devalue version bump
+
+- Add create_story_about_person system pattern with narrative workflow
+- Add heal_person system pattern for compassionate healing plans
+- Update pattern_explanations to register new patterns and renumber indices
+- Extend pattern_descriptions with entries, tags, and concise descriptions
+- Bump devalue dependency from 5.1.1 to 5.3.2
+
+## v1.4.301 (2025-08-28)
+
+### PR [#1735](https://github.com/danielmiessler/Fabric/pull/1735) by [ksylvan](https://github.com/ksylvan): Fix Docker Build Path Configuration
+
+- Fix: update Docker workflow to use specific Dockerfile and monitor markdown file changes
+- Add explicit Dockerfile path to Docker build action
+- Remove markdown files from workflow paths-ignore filter
+- Enable CI triggers for documentation file changes
+- Specify Docker build context with custom file location
+
+## v1.4.300 (2025-08-28)
+
+### PR [#1732](https://github.com/danielmiessler/Fabric/pull/1732) by [ksylvan](https://github.com/ksylvan): CI Infra: Changelog Generation Tool + Docker Image Pubishing
+
+- Add GitHub Actions workflow to publish Docker images on tags
+- Build multi-arch images with Buildx and QEMU across amd64, arm64
+- Tag images using semver; push to GHCR and Docker Hub
+- Gate patterns workflow steps on detected changes instead of failing
+- Auto-detect GitHub owner and repo from git remote URL
+
+## v1.4.299 (2025-08-27)
+
+### PR [#1731](https://github.com/danielmiessler/Fabric/pull/1731) by [ksylvan](https://github.com/ksylvan): chore: upgrade ollama dependency from v0.9.0 to v0.11.7
+
+- Updated ollama package from version 0.9.0 to 0.11.7
+- Fixed 8 security vulnerabilities including 5 high-severity CVEs that could cause denial of service attacks
+- Patched Ollama server vulnerabilities related to division by zero errors and memory exhaustion
+- Resolved security flaws that allowed malicious GGUF model file uploads to crash the server
+- Enhanced system stability and security posture through comprehensive dependency upgrade
+
+## v1.4.298 (2025-08-27)
+
+### PR [#1730](https://github.com/danielmiessler/Fabric/pull/1730) by [ksylvan](https://github.com/ksylvan): Modernize Dockerfile with Best Practices Implementation
+
+- Remove docker-test framework and simplify production docker setup by eliminating complex testing infrastructure
+- Delete entire docker-test directory including test runner scripts and environment configuration files
+- Implement multi-stage build optimization in production Dockerfile to improve build efficiency
+- Remove docker-compose.yml and start-docker.sh helper scripts to streamline container workflow
+- Update README documentation with cleaner Docker usage instructions and reduced image size benefits
+
+## v1.4.297 (2025-08-26)
+
+### PR [#1729](https://github.com/danielmiessler/Fabric/pull/1729) by [ksylvan](https://github.com/ksylvan): Add GitHub Community Health Documents
+
+- Add CODE_OF_CONDUCT defining respectful, collaborative community behavior
+- Add CONTRIBUTING with setup, testing, PR, changelog requirements
+- Add SECURITY policy with reporting process and response timelines
+- Add SUPPORT guide for bugs, features, discussions, expectations
+- Add docs README indexing guides, quick starts, contributor essentials
+
+## v1.4.296 (2025-08-26)
+
+### PR [#1728](https://github.com/danielmiessler/Fabric/pull/1728) by [ksylvan](https://github.com/ksylvan): Refactor Logging System to Use Centralized Debug Logger
+
+- Replace fmt.Fprintf/os.Stderr with centralized debuglog.Log across CLI and add unconditional Log function for important messages
+- Improve OAuth flow messaging and token refresh diagnostics with better error handling
+- Update tests to capture debuglog output via SetOutput for better test coverage
+- Convert Perplexity streaming errors to unified debug logging and emit file write notifications through debuglog
+- Standardize extension registry warnings and announce large audio processing steps via centralized logger
+
+## v1.4.295 (2025-08-24)
+
+### PR [#1727](https://github.com/danielmiessler/Fabric/pull/1727) by [ksylvan](https://github.com/ksylvan): Standardize Anthropic Beta Failure Logging
+
+- Refactor: route Anthropic beta failure logs through internal debug logger
+- Replace fmt.Fprintf stderr with debuglog.Debug for beta failures
+- Import internal log package and remove os dependency
+- Standardize logging level to debuglog.Basic for beta errors
+- Preserve fallback stream behavior when beta features fail
+
+## v1.4.294 (2025-08-20)
+
+### PR [#1723](https://github.com/danielmiessler/Fabric/pull/1723) by [ksylvan](https://github.com/ksylvan): docs: update README with Venice AI provider and Windows install script
+
+- Add Venice AI provider configuration with API endpoint
+- Document Venice AI as privacy-first open-source provider
+- Include PowerShell installation script for Windows users
+- Add debug levels section to table of contents
+- Update recent major features with v1.4.294 release notes
+
+## v1.4.293 (2025-08-19)
+
+### PR [#1718](https://github.com/danielmiessler/Fabric/pull/1718) by [ksylvan](https://github.com/ksylvan): Implement Configurable Debug Logging Levels
+
+- Add --debug flag controlling runtime logging verbosity levels
+- Introduce internal/log package with Off, Basic, Detailed, Trace
+- Replace ad-hoc Debugf and globals with centralized debug logger
+- Wire debug level during early CLI argument parsing
+- Add bash, zsh, fish completions for --debug levels
+
+## v1.4.292 (2025-08-18)
+
+### PR [#1717](https://github.com/danielmiessler/Fabric/pull/1717) by [ksylvan](https://github.com/ksylvan): Highlight default vendor/model in model listing
+
+- Update PrintWithVendor signature to accept default vendor and model
+- Mark default vendor/model with asterisk in non-shell output
+- Compare vendor and model case-insensitively when marking
+- Pass registry defaults to PrintWithVendor from CLI
+- Add test ensuring default selection appears with asterisk
+### Direct commits
+
+- Docs: update version number in README updates section from v1.4.290 to v1.4.291
+
+## v1.4.291 (2025-08-18)
+
+### PR [#1715](https://github.com/danielmiessler/Fabric/pull/1715) by [ksylvan](https://github.com/ksylvan): feat: add speech-to-text via OpenAI with transcription flags and comp…
+
+- Add --transcribe-file flag to transcribe audio or video
+- Add --transcribe-model flag with model listing and completion
+- Add --split-media-file flag to chunk files over 25MB
+- Implement OpenAI transcription using Whisper and GPT-4o Transcribe
+- Integrate transcription pipeline into CLI before readability processing
+
+## v1.4.290 (2025-08-17)
+
+### PR [#1714](https://github.com/danielmiessler/Fabric/pull/1714) by [ksylvan](https://github.com/ksylvan): feat: add per-pattern model mapping support via environment variables
+
+- Add per-pattern model mapping support via environment variables
+- Implement environment variable lookup for pattern-specific models
+- Support vendor|model format in environment variable specification
+- Enable shell startup file configuration for patterns
+- Transform pattern names to uppercase environment variable format
+
+## v1.4.289 (2025-08-16)
+
+### PR [#1710](https://github.com/danielmiessler/Fabric/pull/1710) by [ksylvan](https://github.com/ksylvan): feat: add --no-variable-replacement flag to disable pattern variable …
+
+- Add --no-variable-replacement flag to disable pattern variable substitution
+- Introduce CLI flag to skip pattern variable replacement and wire it into domain request and session builder
+- Provide PatternsEntity.GetWithoutVariables for input-only pattern processing support
+- Refactor patterns code into reusable load and apply helpers
+- Update bash, zsh, fish completions with new flag and document in README and CLI help output
+
+## v1.4.288 (2025-08-16)
+
+### PR [#1709](https://github.com/danielmiessler/Fabric/pull/1709) by [ksylvan](https://github.com/ksylvan): Enhanced YouTube Subtitle Language Fallback Handling
+
+- Fix: improve YouTube subtitle language fallback handling in yt-dlp integration
+- Fix typo "Gemmini" to "Gemini" in README
+- Add "kballard" and "shellquote" to VSCode dictionary
+- Add "YTDLP" to VSCode spell checker
+- Enhance subtitle language options with fallback variants
+
+## v1.4.287 (2025-08-14)
+
+### PR [#1706](https://github.com/danielmiessler/Fabric/pull/1706) by [ksylvan](https://github.com/ksylvan): Gemini Thinking Support and README (New Features) automation
+
+- Add comprehensive "Recent Major Features" section to README
+- Introduce new readme_updates Python script for automation
+- Enable Gemini thinking configuration with token budgets
+- Update CLI help text for Gemini thinking support
+- Add comprehensive test coverage for Gemini thinking
+
+## v1.4.286 (2025-08-14)
+
+### PR [#1700](https://github.com/danielmiessler/Fabric/pull/1700) by [ksylvan](https://github.com/ksylvan): Introduce Thinking Config Across Anthropic and OpenAI Providers
+
+- Add --thinking CLI flag for configurable reasoning levels across providers
+- Implement Anthropic ThinkingConfig with standardized budgets and tokens
+- Map OpenAI reasoning effort from thinking levels
+- Show thinking level in dry-run formatted options
+- Overhaul suggest_pattern docs with categories, workflows, usage examples
+
+## v1.4.285 (2025-08-13)
+
+### PR [#1698](https://github.com/danielmiessler/Fabric/pull/1698) by [ksylvan](https://github.com/ksylvan): Enable One Million Token Context Beta Feature for Sonnet-4
+
+- Chore: upgrade anthropic-sdk-go to v1.9.1 and add beta feature support for context-1m
+- Add modelBetas map for beta feature configuration
+- Implement context-1m-2025-08-07 beta for Claude Sonnet 4
+- Add beta header support with fallback handling
+- Preserve existing beta headers in OAuth transport
+
+## v1.4.284 (2025-08-12)
+
+### PR [#1695](https://github.com/danielmiessler/Fabric/pull/1695) by [ksylvan](https://github.com/ksylvan): Introduce One-Liner Curl Install for Completions
+
+- Add one-liner curl install method for shell completions without requiring repository cloning
+- Support downloading completions when files are missing locally with dry-run option for previewing changes
+- Enable custom download source via environment variable and create temporary directory for downloaded completion files
+- Add automatic cleanup of temporary files and validate downloaded files are non-empty and not HTML
+- Improve error handling and standardize logging by routing informational messages to stderr to avoid stdout pollution
+
 ## v1.4.283 (2025-08-12)
 
 ### PR [#1692](https://github.com/danielmiessler/Fabric/pull/1692) by [ksylvan](https://github.com/ksylvan): Add Vendor Selection Support for Models

README.md

@@ -47,6 +47,55 @@ It's all really exciting and powerful, but _it's not easy to integrate this func
 
 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!
 
+## Updates
+
+Dear Users,
+
+We've been doing so many exciting things here at Fabric, I wanted to give a quick summary here to give you a sense of our development velocity!
+
+Below are the **new features and capabilities** we've added (newest first):
+
+### Recent Major Features
+
+- [v1.4.303](https://github.com/danielmiessler/fabric/releases/tag/v1.4.303) (Aug 29, 2025) — **New Binary Releases**: Linux ARM and Windows ARM targets. You can run Fabric on the Raspberry PI and on your Windows Surface!
+- [v1.4.294](https://github.com/danielmiessler/fabric/releases/tag/v1.4.294) (Aug 20, 2025) — **Venice AI Support**: Added the Venice AI provider. Venice is a Privacy-First, Open-Source AI provider. See their ["About Venice"](https://docs.venice.ai/overview/about-venice) page for details.
+- [v1.4.291](https://github.com/danielmiessler/fabric/releases/tag/v1.4.291) (Aug 18, 2025) — **Speech To Text**: Add OpenAI speech-to-text support with `--transcribe-file`, `--transcribe-model`, and `--split-media-file` flags.
+- [v1.4.287](https://github.com/danielmiessler/fabric/releases/tag/v1.4.287) (Aug 16, 2025) — **AI Reasoning**: Add Thinking to Gemini models and introduce `readme_updates` python script
+- [v1.4.286](https://github.com/danielmiessler/fabric/releases/tag/v1.4.286) (Aug 14, 2025) — **AI Reasoning**: Introduce Thinking Config Across Anthropic and OpenAI Providers
+- [v1.4.285](https://github.com/danielmiessler/fabric/releases/tag/v1.4.285) (Aug 13, 2025) — **Extended Context**: Enable One Million Token Context Beta Feature for Sonnet-4
+- [v1.4.284](https://github.com/danielmiessler/fabric/releases/tag/v1.4.284) (Aug 12, 2025) — **Easy Shell Completions Setup**: Introduce One-Liner Curl Install for Completions
+- [v1.4.283](https://github.com/danielmiessler/fabric/releases/tag/v1.4.283) (Aug 12, 2025) — **Model Management**: Add Vendor Selection Support for Models
+- [v1.4.282](https://github.com/danielmiessler/fabric/releases/tag/v1.4.282) (Aug 11, 2025) — **Enhanced Shell Completions**: Enhanced Shell Completions for Fabric CLI Binaries
+- [v1.4.281](https://github.com/danielmiessler/fabric/releases/tag/v1.4.281) (Aug 11, 2025) — **Gemini Search Tool**: Add Web Search Tool Support for Gemini Models
+- [v1.4.278](https://github.com/danielmiessler/fabric/releases/tag/v1.4.278) (Aug 9, 2025) — **Enhance YouTube Transcripts**: Enhance YouTube Support with Custom yt-dlp Arguments
+- [v1.4.277](https://github.com/danielmiessler/fabric/releases/tag/v1.4.277) (Aug 8, 2025) — **Desktop Notifications**: Add cross-platform desktop notifications to Fabric CLI
+- [v1.4.274](https://github.com/danielmiessler/fabric/releases/tag/v1.4.274) (Aug 7, 2025) — **Claude 4.1 Added**: Add Support for Claude Opus 4.1 Model
+- [v1.4.271](https://github.com/danielmiessler/fabric/releases/tag/v1.4.271) (Jul 28, 2025) — **AI Summarized Release Notes**: Enable AI summary updates for GitHub releases
+- [v1.4.268](https://github.com/danielmiessler/fabric/releases/tag/v1.4.268) (Jul 26, 2025) — **Gemini TTS Voice Selection**: add Gemini TTS voice selection and listing functionality
+- [v1.4.267](https://github.com/danielmiessler/fabric/releases/tag/v1.4.267) (Jul 26, 2025) — **Text-to-Speech**: Update Gemini Plugin to New SDK with TTS Support
+- [v1.4.258](https://github.com/danielmiessler/fabric/releases/tag/v1.4.258) (Jul 17, 2025) — **Onboarding Improved**: Add startup check to initialize config and .env file automatically
+- [v1.4.257](https://github.com/danielmiessler/fabric/releases/tag/v1.4.257) (Jul 17, 2025) — **OpenAI Routing Control**: Introduce CLI Flag to Disable OpenAI Responses API
+- [v1.4.252](https://github.com/danielmiessler/fabric/releases/tag/v1.4.252) (Jul 16, 2025) — **Hide Thinking Block**: Optional Hiding of Model Thinking Process with Configurable Tags
+- [v1.4.246](https://github.com/danielmiessler/fabric/releases/tag/v1.4.246) (Jul 14, 2025) — **Automatic ChangeLog Updates**: Add AI-powered changelog generation with high-performance Go tool and comprehensive caching
+- [v1.4.245](https://github.com/danielmiessler/fabric/releases/tag/v1.4.245) (Jul 11, 2025) — **Together AI**: Together AI Support with OpenAI Fallback Mechanism Added
+- [v1.4.232](https://github.com/danielmiessler/fabric/releases/tag/v1.4.232) (Jul 6, 2025) — **Add Custom**: Add Custom Patterns Directory Support
+- [v1.4.231](https://github.com/danielmiessler/fabric/releases/tag/v1.4.231) (Jul 5, 2025) — **OAuth Auto-Auth**: OAuth Authentication Support for Anthropic (Use your Max Subscription)
+- [v1.4.230](https://github.com/danielmiessler/fabric/releases/tag/v1.4.230) (Jul 5, 2025) — **Model Management**: Add advanced image generation parameters for OpenAI models with four new CLI flags
+- [v1.4.227](https://github.com/danielmiessler/fabric/releases/tag/v1.4.227) (Jul 4, 2025) — **Add Image**: Add Image Generation Support to Fabric
+- [v1.4.226](https://github.com/danielmiessler/fabric/releases/tag/v1.4.226) (Jul 4, 2025) — **Web Search**: OpenAI Plugin Now Supports Web Search Functionality
+- [v1.4.225](https://github.com/danielmiessler/fabric/releases/tag/v1.4.225) (Jul 4, 2025) — **Web Search**: Runtime Web Search Control via Command-Line `--search` Flag
+- [v1.4.224](https://github.com/danielmiessler/fabric/releases/tag/v1.4.224) (Jul 1, 2025) — **Add code_review**: Add code_review pattern and updates in Pattern_Descriptions
+- [v1.4.222](https://github.com/danielmiessler/fabric/releases/tag/v1.4.222) (Jul 1, 2025) — **OpenAI Plugin**: OpenAI Plugin Migrates to New Responses API
+- [v1.4.218](https://github.com/danielmiessler/fabric/releases/tag/v1.4.218) (Jun 27, 2025) — **Model Management**: Add Support for OpenAI Search and Research Model Variants
+- [v1.4.217](https://github.com/danielmiessler/fabric/releases/tag/v1.4.217) (Jun 26, 2025) — **New YouTube**: New YouTube Transcript Endpoint Added to REST API
+- [v1.4.212](https://github.com/danielmiessler/fabric/releases/tag/v1.4.212) (Jun 23, 2025) — **Add Langdock**: Add Langdock AI and enhance generic OpenAI compatible support
+- [v1.4.211](https://github.com/danielmiessler/fabric/releases/tag/v1.4.211) (Jun 19, 2025) — **REST API**: REST API and Web UI Now Support Dynamic Pattern Variables
+- [v1.4.210](https://github.com/danielmiessler/fabric/releases/tag/v1.4.210) (Jun 18, 2025) — **Add Citations**: Add Citation Support to Perplexity Response
+- [v1.4.208](https://github.com/danielmiessler/fabric/releases/tag/v1.4.208) (Jun 17, 2025) — **Add Perplexity**: Add Perplexity AI Provider with Token Limits Support
+- [v1.4.203](https://github.com/danielmiessler/fabric/releases/tag/v1.4.203) (Jun 14, 2025) — **Add Amazon Bedrock**: Add support for Amazon Bedrock
+
+These features represent our commitment to making Fabric the most powerful and flexible AI augmentation framework available!
+
 ## 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.
@@ -60,9 +109,11 @@ Keep in mind that many of these were recorded when Fabric was Python-based, so r
 
 - [`fabric`](#fabric)
   - [What and why](#what-and-why)
+  - [Updates](#updates)
+    - [Recent Major Features](#recent-major-features)
   - [Intro videos](#intro-videos)
   - [Navigation](#navigation)
-  - [Updates](#updates)
+  - [Changelog](#changelog)
   - [Philosophy](#philosophy)
     - [Breaking problems into components](#breaking-problems-into-components)
     - [Too many prompts](#too-many-prompts)
@@ -76,18 +127,23 @@ Keep in mind that many of these were recorded when Fabric was Python-based, so r
     - [Using package managers](#using-package-managers)
       - [macOS (Homebrew)](#macos-homebrew)
       - [Arch Linux (AUR)](#arch-linux-aur)
+      - [Windows](#windows-1)
     - [From Source](#from-source)
+    - [Docker](#docker)
     - [Environment Variables](#environment-variables)
     - [Setup](#setup)
+    - [Per-Pattern Model Mapping](#per-pattern-model-mapping)
     - [Add aliases for all patterns](#add-aliases-for-all-patterns)
       - [Save your files in markdown using aliases](#save-your-files-in-markdown-using-aliases)
     - [Migration](#migration)
     - [Upgrading](#upgrading)
     - [Shell Completions](#shell-completions)
+      - [Quick install (no clone required)](#quick-install-no-clone-required)
       - [Zsh Completion](#zsh-completion)
       - [Bash Completion](#bash-completion)
       - [Fish Completion](#fish-completion)
   - [Usage](#usage)
+    - [Debug Levels](#debug-levels)
   - [Our approach to prompting](#our-approach-to-prompting)
   - [Examples](#examples)
   - [Just use the Patterns](#just-use-the-patterns)
@@ -111,7 +167,7 @@ Keep in mind that many of these were recorded when Fabric was Python-based, so r
 
 <br />
 
-## Updates
+## Changelog
 
 Fabric is evolving rapidly.
 
@@ -156,7 +212,16 @@ To install Fabric, you can use the latest release binaries or install it from th
 
 #### Windows
 
-`https://github.com/danielmiessler/fabric/releases/latest/download/fabric-windows-amd64.exe`
+Via PowerShell, just copy and paste and run the following snippet to install the binary into `{HOME}\.local\bin`. Please make sure that directory is included in your `PATH`.
+
+```powershell
+$ErrorActionPreference = "Stop"
+$LATEST="https://github.com/danielmiessler/fabric/releases/latest/download/fabric-windows-amd64.exe"
+$DIR="${HOME}\.local\bin"
+New-Item -Path $DIR -ItemType Directory -Force
+Invoke-WebRequest -URI  "${LATEST}" -outfile "${DIR}\fabric.exe"
+& "${DIR}\fabric.exe" /version
+```
 
 #### macOS (arm64)
 
@@ -191,6 +256,12 @@ alias fabric='fabric-ai'
 
 `yay -S fabric-ai`
 
+#### Windows
+
+Use the official Microsoft supported `Winget` tool:
+
+`winget install danielmiessler.Fabric`
+
 ### From Source
 
 To install Fabric, [make sure Go is installed](https://go.dev/doc/install), and then run the following command.
@@ -200,6 +271,35 @@ To install Fabric, [make sure Go is installed](https://go.dev/doc/install), and
 go install github.com/danielmiessler/fabric/cmd/fabric@latest
 ```
 
+### Docker
+
+Run Fabric using pre-built Docker images:
+
+```bash
+# Use latest image from Docker Hub
+docker run --rm -it kayvan/fabric:latest --version
+
+# Use specific version from GHCR
+docker run --rm -it ghcr.io/ksylvan/fabric:v1.4.305 --version
+
+# Run setup (first time)
+mkdir -p $HOME/.fabric-config
+docker run --rm -it -v $HOME/.fabric-config:/root/.config/fabric kayvan/fabric:latest --setup
+
+# Use Fabric with your patterns
+docker run --rm -it -v $HOME/.fabric-config:/root/.config/fabric kayvan/fabric:latest -p summarize
+
+# Run the REST API server
+docker run --rm -it -p 8080:8080 -v $HOME/.fabric-config:/root/.config/fabric kayvan/fabric:latest --serve
+```
+
+**Images available at:**
+
+- Docker Hub: [kayvan/fabric](https://hub.docker.com/repository/docker/kayvan/fabric/general)
+- GHCR: [ksylvan/fabric](https://github.com/ksylvan/fabric/pkgs/container/fabric)
+
+See [scripts/docker/README.md](./scripts/docker/README.md) for building custom images and advanced configuration.
+
 ### Environment Variables
 
 You may need to set some environment variables in your `~/.bashrc` on linux or `~/.zshrc` file on mac to be able to run the `fabric` command. Here is an example of what you can add:
@@ -235,6 +335,13 @@ fabric --setup
 
 If everything works you are good to go.
 
+### Per-Pattern Model Mapping
+
+ You can configure specific models for individual patterns using environment variables
+ like `FABRIC_MODEL_PATTERN_NAME=vendor|model`
+
+ This makes it easy to maintain these per-pattern model mappings in your shell startup files.
+
 ### Add aliases for all patterns
 
 In order to add aliases for all your patterns and use them directly as commands ie. `summarize` instead of `fabric --pattern summarize`
@@ -428,6 +535,25 @@ 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.
 
+#### Quick install (no clone required)
+
+You can install completions directly via a one-liner:
+
+```bash
+curl -fsSL https://raw.githubusercontent.com/danielmiessler/Fabric/refs/heads/main/completions/setup-completions.sh | sh
+```
+
+Optional variants:
+
+```bash
+# Dry-run (see actions without changing your system)
+curl -fsSL https://raw.githubusercontent.com/danielmiessler/Fabric/refs/heads/main/completions/setup-completions.sh | sh -s -- --dry-run
+
+# Override the download source (advanced)
+FABRIC_COMPLETIONS_BASE_URL="https://raw.githubusercontent.com/danielmiessler/Fabric/refs/heads/main/completions" \
+    sh -c "$(curl -fsSL https://raw.githubusercontent.com/danielmiessler/Fabric/refs/heads/main/completions/setup-completions.sh)"
+```
+
 #### Zsh Completion
 
 To enable Zsh completion:
@@ -523,6 +649,7 @@ Application Options:
       --printsession=               Print session
       --readability                 Convert HTML input into a clean, readable view
       --input-has-vars              Apply variables to user input
+      --no-variable-replacement     Disable pattern variable replacement
       --dry-run                     Show what would be sent to the model without actually sending it
       --serve                       Serve the Fabric Rest API
       --serveOllama                 Serve the Fabric Rest API with ollama endpoints
@@ -556,11 +683,22 @@ Application Options:
       --notification-command=       Custom command to run for notifications (overrides built-in
                                     notifications)
       --yt-dlp-args=                Additional arguments to pass to yt-dlp (e.g. '--cookies-from-browser brave')
-
+      --thinking=                   Set reasoning/thinking level (e.g., off, low, medium, high, or
+                                    numeric tokens for Anthropic or Google Gemini)
+      --debug=                     Set debug level (0: off, 1: basic, 2: detailed, 3: trace)
 Help Options:
   -h, --help                        Show this help message
 ```
 
+### Debug Levels
+
+Use the `--debug` flag to control runtime logging:
+
+- `0`: off (default)
+- `1`: basic debug info
+- `2`: detailed debugging
+- `3`: trace level
+
 ## Our approach to prompting
 
 Fabric _Patterns_ are different than most prompts you'll see.
@@ -570,7 +708,7 @@ Fabric _Patterns_ are different than most prompts you'll see.
 Here's an example of a Fabric Pattern.
 
 ```bash
-https://github.com/danielmiessler/fabric/blob/main/patterns/extract_wisdom/system.md
+https://github.com/danielmiessler/Fabric/blob/main/data/patterns/extract_wisdom/system.md
 ```
 
 <img width="1461" alt="pattern-example" src="https://github.com/danielmiessler/fabric/assets/50654/b910c551-9263-405f-9735-71ca69bbab6d">

cmd/fabric/version.go

@@ -1,3 +1,3 @@
 package main
 
-var version = "v1.4.283"
+var version = "v1.4.306"

cmd/generate_changelog/internal/release.go

@@ -3,6 +3,9 @@ package internal
 import (
 	"context"
 	"fmt"
+	"os/exec"
+	"regexp"
+	"strings"
 
 	"github.com/danielmiessler/fabric/cmd/generate_changelog/internal/cache"
 	"github.com/danielmiessler/fabric/cmd/generate_changelog/internal/config"
@@ -17,17 +20,50 @@ type ReleaseManager struct {
 	repo        string
 }
 
+// getGitHubInfo extracts owner and repo from git remote origin URL
+func getGitHubInfo() (owner, repo string, err error) {
+	cmd := exec.Command("git", "remote", "get-url", "origin")
+	output, err := cmd.Output()
+	if err != nil {
+		return "", "", fmt.Errorf("failed to get git remote URL: %w", err)
+	}
+
+	url := strings.TrimSpace(string(output))
+
+	// Handle both SSH and HTTPS URLs
+	// SSH: git@github.com:owner/repo.git
+	// HTTPS: https://github.com/owner/repo.git
+	var re *regexp.Regexp
+	if strings.HasPrefix(url, "git@") {
+		re = regexp.MustCompile(`git@github\.com:([^/]+)/([^/.]+)(?:\.git)?`)
+	} else {
+		re = regexp.MustCompile(`https://github\.com/([^/]+)/([^/.]+)(?:\.git)?`)
+	}
+
+	matches := re.FindStringSubmatch(url)
+	if len(matches) < 3 {
+		return "", "", fmt.Errorf("invalid GitHub URL format: %s", url)
+	}
+
+	return matches[1], matches[2], nil
+}
+
 func NewReleaseManager(cfg *config.Config) (*ReleaseManager, error) {
 	cache, err := cache.New(cfg.CacheFile)
 	if err != nil {
 		return nil, fmt.Errorf("failed to create cache: %w", err)
 	}
 
+	owner, repo, err := getGitHubInfo()
+	if err != nil {
+		return nil, fmt.Errorf("failed to get GitHub repository info: %w", err)
+	}
+
 	return &ReleaseManager{
 		cache:       cache,
 		githubToken: cfg.GitHubToken,
-		owner:       "danielmiessler",
-		repo:        "fabric",
+		owner:       owner,
+		repo:        repo,
 	}, nil
 }
 
@@ -65,17 +101,49 @@ func (rm *ReleaseManager) UpdateReleaseDescription(version string) error {
 		client = github.NewClient(nil)
 	}
 
-	release, _, err := client.Repositories.GetReleaseByTag(ctx, rm.owner, rm.repo, version)
+	// Check if current repository is a fork by getting repo details
+	repo, _, err := client.Repositories.Get(ctx, rm.owner, rm.repo)
+	if err != nil {
+		return fmt.Errorf("failed to get repository info: %w", err)
+	}
+
+	// If repository is a fork, try updating the upstream (parent) repository first
+	if repo.Parent != nil {
+		parentOwner := repo.Parent.Owner.GetLogin()
+		parentRepo := repo.Parent.GetName()
+
+		fmt.Printf("Repository is a fork of %s/%s, attempting to update upstream release...\n", parentOwner, parentRepo)
+
+		err := rm.updateReleaseForRepo(ctx, client, parentOwner, parentRepo, version, releaseBody)
+		if err == nil {
+			fmt.Printf("Successfully updated release description for %s in upstream repository %s/%s\n", version, parentOwner, parentRepo)
+			return nil
+		}
+
+		fmt.Printf("Failed to update upstream repository: %v\nFalling back to current repository...\n", err)
+	}
+
+	// Update current repository (either not a fork or upstream update failed)
+	err = rm.updateReleaseForRepo(ctx, client, rm.owner, rm.repo, version, releaseBody)
+	if err != nil {
+		return fmt.Errorf("failed to update release description for version %s in repository %s/%s: %w", version, rm.owner, rm.repo, err)
+	}
+
+	fmt.Printf("Successfully updated release description for %s in repository %s/%s\n", version, rm.owner, rm.repo)
+	return nil
+}
+
+func (rm *ReleaseManager) updateReleaseForRepo(ctx context.Context, client *github.Client, owner, repo, version, releaseBody string) error {
+	release, _, err := client.Repositories.GetReleaseByTag(ctx, owner, repo, version)
 	if err != nil {
 		return fmt.Errorf("failed to get release for version %s: %w", version, err)
 	}
 
 	release.Body = &releaseBody
-	_, _, err = client.Repositories.EditRelease(ctx, rm.owner, rm.repo, *release.ID, release)
+	_, _, err = client.Repositories.EditRelease(ctx, owner, repo, *release.ID, release)
 	if err != nil {
 		return fmt.Errorf("failed to update release description for version %s: %w", version, err)
 	}
 
-	fmt.Printf("Successfully updated release description for %s\n", version)
 	return nil
 }

completions/_fabric

@@ -59,6 +59,13 @@ _fabric_gemini_voices() {
   compadd -X "Gemini TTS Voices:" ${voices}
 }
 
+_fabric_transcription_models() {
+  local -a models
+  local cmd=${words[1]}
+  models=(${(f)"$($cmd --list-transcription-models --shell-complete-list 2>/dev/null)"})
+  compadd -X "Transcription Models:" ${models}
+}
+
 _fabric() {
   local curcontext="$curcontext" state line
   typeset -A opt_args
@@ -100,12 +107,14 @@ _fabric() {
     '(-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:' \
+    '(--thinking)--thinking[Set reasoning/thinking level]:level:(off low medium high)' \
     '(-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]' \
+    '(--no-variable-replacement)--no-variable-replacement[Disable pattern variable replacement]' \
     '(--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]' \
@@ -133,6 +142,10 @@ _fabric() {
     '(--think-start-tag)--think-start-tag[Start tag for thinking sections (default: <think>)]:start tag:' \
     '(--think-end-tag)--think-end-tag[End tag for thinking sections (default: </think>)]:end tag:' \
     '(--disable-responses-api)--disable-responses-api[Disable OpenAI Responses API (default: false)]' \
+    '(--transcribe-file)--transcribe-file[Audio or video file to transcribe]:audio file:_files -g "*.mp3 *.mp4 *.mpeg *.mpga *.m4a *.wav *.webm"' \
+    '(--transcribe-model)--transcribe-model[Model to use for transcription (separate from chat model)]:transcribe model:_fabric_transcription_models' \
+    '(--split-media-file)--split-media-file[Split audio/video files larger than 25MB using ffmpeg]' \
+    '(--debug)--debug[Set debug level (0=off, 1=basic, 2=detailed, 3=trace)]:debug level:(0 1 2 3)' \
     '(--notification)--notification[Send desktop notification when command completes]' \
     '(--notification-command)--notification-command[Custom command to run for notifications]:notification command:' \
     '(-h --help)'{-h,--help}'[Show this help message]' \

completions/fabric.bash

@@ -13,7 +13,7 @@ _fabric() {
   _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 --vendor -V --modelContextLength --output -o --output-session --latest -n --changeDefaultModel -d --youtube -y --playlist --transcript --transcript-with-timestamps --comments --metadata --yt-dlp-args --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 --search --search-location --image-file --image-size --image-quality --image-compression --image-background --suppress-think --think-start-tag --think-end-tag --disable-responses-api --voice --list-gemini-voices --notification --notification-command --version --listextensions --addextension --rmextension --strategy --liststrategies --listvendors --shell-complete-list --help -h"
+  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 --vendor -V --modelContextLength --output -o --output-session --latest -n --changeDefaultModel -d --youtube -y --playlist --transcript --transcript-with-timestamps --comments --metadata --yt-dlp-args --language -g --scrape_url -u --scrape_question -q --seed -e --thinking --wipecontext -w --wipesession -W --printcontext --printsession --readability --input-has-vars --no-variable-replacement --dry-run --serve --serveOllama --address --api-key --config --search --search-location --image-file --image-size --image-quality --image-compression --image-background --suppress-think --think-start-tag --think-end-tag --disable-responses-api --transcribe-file --transcribe-model --split-media-file --voice --list-gemini-voices --notification --notification-command --debug --version --listextensions --addextension --rmextension --strategy --liststrategies --listvendors --shell-complete-list --help -h"
 
   # Helper function for dynamic completions
   _fabric_get_list() {
@@ -58,6 +58,10 @@ _fabric() {
     COMPREPLY=($(compgen -W "$(_fabric_get_list --listsessions)" -- "${cur}"))
     return 0
     ;;
+  --thinking)
+    COMPREPLY=($(compgen -W "off low medium high" -- "${cur}"))
+    return 0
+    ;;
   --rmextension)
     COMPREPLY=($(compgen -W "$(_fabric_get_list --listextensions)" -- "${cur}"))
     return 0
@@ -70,8 +74,16 @@ _fabric() {
     COMPREPLY=($(compgen -W "$(_fabric_get_list --list-gemini-voices)" -- "${cur}"))
     return 0
     ;;
+  --transcribe-model)
+    COMPREPLY=($(compgen -W "$(_fabric_get_list --list-transcription-models)" -- "${cur}"))
+    return 0
+    ;;
+  --debug)
+    COMPREPLY=($(compgen -W "0 1 2 3" -- "${cur}"))
+    return 0
+    ;;
   # Options requiring file/directory paths
-  -a | --attachment | -o | --output | --config | --addextension | --image-file)
+  -a | --attachment | -o | --output | --config | --addextension | --image-file | --transcribe-file)
     _filedir
     return 0
     ;;

completions/fabric.fish

@@ -47,6 +47,11 @@ function __fabric_get_gemini_voices
         $cmd --list-gemini-voices --shell-complete-list 2>/dev/null
 end
 
+function __fabric_get_transcription_models
+        set cmd (commandline -opc)[1]
+        $cmd --list-transcription-models --shell-complete-list 2>/dev/null
+end
+
 # Main completion function
 function __fabric_register_completions
         set cmd $argv[1]
@@ -72,6 +77,7 @@ function __fabric_register_completions
         complete -c $cmd -s u -l scrape_url -d "Scrape website URL to markdown using Jina AI"
         complete -c $cmd -s q -l scrape_question -d "Search question using Jina AI"
         complete -c $cmd -s e -l seed -d "Seed to be used for LMM generation"
+        complete -c $cmd -l thinking -d "Set reasoning/thinking level" -a "off low medium high"
         complete -c $cmd -s w -l wipecontext -d "Wipe context" -a "(__fabric_get_contexts)"
         complete -c $cmd -s W -l wipesession -d "Wipe session" -a "(__fabric_get_sessions)"
         complete -c $cmd -l printcontext -d "Print context" -a "(__fabric_get_contexts)"
@@ -91,6 +97,9 @@ function __fabric_register_completions
         complete -c $cmd -l think-start-tag -d "Start tag for thinking sections (default: <think>)"
         complete -c $cmd -l think-end-tag -d "End tag for thinking sections (default: </think>)"
         complete -c $cmd -l voice -d "TTS voice name for supported models (e.g., Kore, Charon, Puck)" -a "(__fabric_get_gemini_voices)"
+        complete -c $cmd -l transcribe-file -d "Audio or video file to transcribe" -r -a "*.mp3 *.mp4 *.mpeg *.mpga *.m4a *.wav *.webm"
+        complete -c $cmd -l transcribe-model -d "Model to use for transcription (separate from chat model)" -a "(__fabric_get_transcription_models)"
+        complete -c $cmd -l debug -d "Set debug level (0=off, 1=basic, 2=detailed, 3=trace)" -a "0 1 2 3"
         complete -c $cmd -l notification-command -d "Custom command to run for notifications (overrides built-in notifications)"
 
         # Boolean flags (no arguments)
@@ -112,8 +121,9 @@ function __fabric_register_completions
         complete -c $cmd -l metadata -d "Output video metadata"
         complete -c $cmd -l yt-dlp-args -d "Additional arguments to pass to yt-dlp (e.g. '--cookies-from-browser brave')"
         complete -c $cmd -l readability -d "Convert HTML input into a clean, readable view"
-        complete -c $cmd -l input-has-vars -d "Apply variables to user input"
-        complete -c $cmd -l dry-run -d "Show what would be sent to the model without actually sending it"
+       complete -c $cmd -l input-has-vars -d "Apply variables to user input"
+       complete -c $cmd -l no-variable-replacement -d "Disable pattern variable replacement"
+       complete -c $cmd -l dry-run -d "Show what would be sent to the model without actually sending it"
         complete -c $cmd -l search -d "Enable web search tool for supported models (Anthropic, OpenAI, Gemini)"
         complete -c $cmd -l serve -d "Serve the Fabric Rest API"
         complete -c $cmd -l serveOllama -d "Serve the Fabric Rest API with ollama endpoints"
@@ -125,6 +135,7 @@ function __fabric_register_completions
         complete -c $cmd -l shell-complete-list -d "Output raw list without headers/formatting (for shell completion)"
         complete -c $cmd -l suppress-think -d "Suppress text enclosed in thinking tags"
         complete -c $cmd -l disable-responses-api -d "Disable OpenAI Responses API (default: false)"
+        complete -c $cmd -l split-media-file -d "Split audio/video files larger than 25MB using ffmpeg"
         complete -c $cmd -l notification -d "Send desktop notification when command completes"
         complete -c $cmd -s h -l help -d "Show this help message"
 end

completions/setup-completions.sh

@@ -8,6 +8,10 @@ set -e
 
 # Global variables
 DRY_RUN=false
+# Base URL to fetch completion files when not available locally
+# Can be overridden via environment variable FABRIC_COMPLETIONS_BASE_URL
+FABRIC_COMPLETIONS_BASE_URL="${FABRIC_COMPLETIONS_BASE_URL:-https://raw.githubusercontent.com/danielmiessler/Fabric/refs/heads/main/completions}"
+TEMP_DIR=""
 
 # Colors for output
 RED='\033[0;31m'
@@ -50,6 +54,109 @@ execute_command() {
     fi
 }
 
+# Simple downloader that prefers curl, falls back to wget
+to_github_raw_url() {
+    in_url="$1"
+    case "$in_url" in
+        https://github.com/*/*/blob/*)
+            # Convert blob URL to raw
+            # https://github.com/{owner}/{repo}/blob/{ref}/path -> https://raw.githubusercontent.com/{owner}/{repo}/{ref}/path
+            echo "$in_url" | sed -E 's#https://github.com/([^/]+)/([^/]+)/blob/([^/]+)/#https://raw.githubusercontent.com/\1/\2/\3/#'
+            ;;
+        https://github.com/*/*/tree/*)
+            # Convert tree URL base + file path to raw
+            # https://github.com/{owner}/{repo}/tree/{ref}/path -> https://raw.githubusercontent.com/{owner}/{repo}/{ref}/path
+            echo "$in_url" | sed -E 's#https://github.com/([^/]+)/([^/]+)/tree/([^/]+)/#https://raw.githubusercontent.com/\1/\2/\3/#'
+            ;;
+        *)
+            echo "$in_url"
+            ;;
+    esac
+}
+
+# Simple downloader that prefers curl, falls back to wget
+download_file() {
+    url="$1"
+    dest="$2"
+
+    if [ "$DRY_RUN" = true ]; then
+        print_dry_run "Would download: $url -> $dest"
+        return 0
+    fi
+
+    eff_url="$(to_github_raw_url "$url")"
+
+    if command -v curl >/dev/null 2>&1; then
+        curl -fsSL "$eff_url" -o "$dest"
+        return $?
+    elif command -v wget >/dev/null 2>&1; then
+        wget -q "$eff_url" -O "$dest"
+        return $?
+    else
+        print_error "Neither 'curl' nor 'wget' is available to download: $url"
+        return 1
+    fi
+}
+
+# Attempt to obtain completion files. If local copies are missing,
+# download them into a temporary directory and return that directory path.
+obtain_completion_files() {
+    obf_script_dir="$1"
+    obf_need_download=false
+
+    if [ ! -f "$obf_script_dir/_fabric" ] || [ ! -f "$obf_script_dir/fabric.bash" ] || [ ! -f "$obf_script_dir/fabric.fish" ]; then
+        obf_need_download=true
+    fi
+
+    if [ "$obf_need_download" = false ]; then
+        echo "$obf_script_dir"
+        return 0
+    fi
+
+    # Note: write only to stderr in this function except for the final echo which returns the path
+    printf "%s\n" "[INFO] Local completion files not found; will download from GitHub." 1>&2
+    printf "%s\n" "[INFO] Source: $FABRIC_COMPLETIONS_BASE_URL" 1>&2
+
+    if [ "$DRY_RUN" = true ]; then
+    printf "%s\n" "[DRY-RUN] Would create temporary directory for downloads" 1>&2
+    echo "$obf_script_dir" # Keep using original for dry-run copies
+        return 0
+    fi
+
+    TEMP_DIR="$(mktemp -d 2>/dev/null || mktemp -d -t fabric-completions)"
+    if [ ! -d "$TEMP_DIR" ]; then
+    print_error "Failed to create temporary directory for downloads."
+        return 1
+    fi
+
+    if ! download_file "$FABRIC_COMPLETIONS_BASE_URL/_fabric" "$TEMP_DIR/_fabric"; then
+        print_error "Failed to download _fabric"
+        return 1
+    fi
+    if [ ! -s "$TEMP_DIR/_fabric" ] || head -n1 "$TEMP_DIR/_fabric" | grep -qi "^<!DOCTYPE\|^<html"; then
+        print_error "Downloaded _fabric appears invalid (empty or HTML). Check FABRIC_COMPLETIONS_BASE_URL."
+        return 1
+    fi
+    if ! download_file "$FABRIC_COMPLETIONS_BASE_URL/fabric.bash" "$TEMP_DIR/fabric.bash"; then
+        print_error "Failed to download fabric.bash"
+        return 1
+    fi
+    if [ ! -s "$TEMP_DIR/fabric.bash" ] || head -n1 "$TEMP_DIR/fabric.bash" | grep -qi "^<!DOCTYPE\|^<html"; then
+        print_error "Downloaded fabric.bash appears invalid (empty or HTML). Check FABRIC_COMPLETIONS_BASE_URL."
+        return 1
+    fi
+    if ! download_file "$FABRIC_COMPLETIONS_BASE_URL/fabric.fish" "$TEMP_DIR/fabric.fish"; then
+        print_error "Failed to download fabric.fish"
+        return 1
+    fi
+    if [ ! -s "$TEMP_DIR/fabric.fish" ] || head -n1 "$TEMP_DIR/fabric.fish" | grep -qi "^<!DOCTYPE\|^<html"; then
+        print_error "Downloaded fabric.fish appears invalid (empty or HTML). Check FABRIC_COMPLETIONS_BASE_URL."
+        return 1
+    fi
+
+    echo "$TEMP_DIR"
+}
+
 # Ensure directory exists, try sudo on permission failure
 ensure_dir() {
     dir="$1"
@@ -266,6 +373,7 @@ setup_fish_completions() {
 setup_other_shell_completions() {
     fabric_cmd="$1"
     shell_name="$2"
+    script_dir="$3"
 
     print_warning "Shell '$shell_name' is not directly supported."
     print_info "You can manually source the completion files:"
@@ -289,8 +397,14 @@ DESCRIPTION:
     This script automatically installs shell completions for the fabric CLI
     based on your current shell and the installed fabric command name.
 
-    The script looks for completion files in the same directory as the script,
-    so it can be run from anywhere.
+        The script will use completion files from the same directory as the script
+        when available. If they are not present (e.g., when running via curl), it
+        will download them from GitHub:
+
+            $FABRIC_COMPLETIONS_BASE_URL
+
+        You can override the download source by setting
+        FABRIC_COMPLETIONS_BASE_URL to your preferred location.
 
     Supports: zsh, bash, fish
 
@@ -301,9 +415,11 @@ DESCRIPTION:
     4. Try multiple standard completion directories
 
 EXAMPLES:
-    ./setup-completions.sh              # Install completions
-    ./setup-completions.sh --dry-run    # Show what would be done
-    ./setup-completions.sh --help       # Show this help
+        ./setup-completions.sh                  # Install completions
+        ./setup-completions.sh --dry-run        # Show what would be done
+        FABRIC_COMPLETIONS_BASE_URL="https://raw.githubusercontent.com/<owner>/<repo>/main/completions" \\
+            ./setup-completions.sh               # Override download source
+        ./setup-completions.sh --help           # Show this help
 
 EOF
 }
@@ -337,19 +453,19 @@ main() {
         print_info ""
     fi
 
-    # Get script directory
+    # Get script directory and obtain completion files (local or downloaded)
     script_dir="$(get_script_dir)"
-
-    # Check if completion files exist
-    if [ ! -f "$script_dir/_fabric" ] || [ ! -f "$script_dir/fabric.bash" ] || [ ! -f "$script_dir/fabric.fish" ]; then
-        print_error "Completion files not found. Make sure you're running this script from the fabric completions directory."
-        print_error "Expected files:"
-        print_error "  $script_dir/_fabric"
-        print_error "  $script_dir/fabric.bash"
-        print_error "  $script_dir/fabric.fish"
+    script_dir="$(obtain_completion_files "$script_dir" || echo "")"
+    if [ -z "$script_dir" ]; then
+        print_error "Unable to obtain completion files. Aborting."
         exit 1
     fi
 
+    # If we downloaded into a temp dir, arrange cleanup at process exit
+    if [ -n "$TEMP_DIR" ] && [ -d "$TEMP_DIR" ]; then
+        trap 'if [ -n "$TEMP_DIR" ] && [ -d "$TEMP_DIR" ]; then rm -rf "$TEMP_DIR"; fi' EXIT INT TERM
+    fi
+
     # Detect fabric command
     fabric_cmd="$(detect_fabric_command)"
     print_info "Detected fabric command: $fabric_cmd"
@@ -370,7 +486,7 @@ main() {
             setup_fish_completions "$fabric_cmd" "$script_dir"
             ;;
         *)
-            setup_other_shell_completions "$fabric_cmd" "$shell_name"
+            setup_other_shell_completions "$fabric_cmd" "$shell_name" "$script_dir"
             ;;
     esac
 

data/patterns/create_story_about_person/system.md

@@ -0,0 +1,26 @@
+You are an expert creative writer specializing in character-driven narratives, and a keen observer of human psychology. Your task is to craft a compelling, realistic short story based on a psychological profile or personal data provided by the user.
+
+**Input:**
+The user will provide a psychological profile or descriptive data about a fictional or real person. This input will be clearly delimited by triple backticks (```). It may include personality traits, habits, fears, motivations, strengths, weaknesses, background information, or specific behavioral patterns.
+
+**Task Steps:**
+
+1.  **Analyze Profile:** Carefully read and internalize the provided psychological profile. Identify the core personality traits, typical reactions, strengths, and vulnerabilities of the individual.
+2.  **Brainstorm Challenges:** Based on the analysis from Step 1, generate 3-5 common, relatable, everyday problems or minor dilemmas that a person with this specific profile might genuinely encounter. These challenges should be varied and could span social, professional, personal, or emotional domains.
+3.  **Develop Strategies:** For each identified problem from Step 2, devise 1-2 specific, plausible methods or strategies that the character, consistent with their psychological profile, would naturally employ (or attempt to employ) to navigate, cope with, or solve these challenges. Consider both internal thought processes and external actions.
+4.  **Construct Narrative:** Weave these problems and the character's responses into a cohesive, engaging short story (approximately 500-700 words, 3-5 paragraphs). The story should have a clear narrative flow, introducing the character, presenting the challenges, and showing their journey through them.
+5.  **Maintain Consistency:** Throughout the story, ensure the character's actions, dialogue, internal monologue, and emotional reactions are consistently aligned with the psychological profile provided. The story should feel authentic to the character.
+
+**Output Requirements:**
+
+*   **Format:** A continuous narrative short story.
+*   **Tone:** Empathetic, realistic, and engaging.
+*   **Content:** The story must clearly depict the character facing everyday problems and demonstrate their unique methods and strategies for navigating these challenges, directly reflecting the input profile.
+*   **Length:** Approximately 500-700 words.
+*   **Avoid:** Overly dramatic or fantastical scenarios unless the profile explicitly suggests such a context. Focus on the 'everyday common problems'.
+
+**Example of Input Format:**
+
+```
+[Psychological Profile/Data Here]
+```

data/patterns/heal_person/system.md

@@ -0,0 +1,53 @@
+# IDENTITY and PURPOSE
+
+You are an AI assistant whose primary responsibility is to interpret and analyze psychological profiles and/or psychology data files provided as input. Your role is to carefully process this data and use your expertise to develop a tailored plan aimed at spiritual and mental healing, as well as overall life improvement for the subject. You must approach each case with sensitivity, applying psychological knowledge and holistic strategies to create actionable, personalized recommendations that address both mental and spiritual well-being. Your focus is on structured, compassionate, and practical guidance that can help the individual make meaningful improvements in their life.
+
+Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
+
+# STEPS
+
+- Carefully review the psychological-profile and/or psychology data file provided as input.
+
+- Analyze the data to identify key issues, strengths, and areas needing improvement related to the subject's mental and spiritual well-being.
+
+- Develop a comprehensive plan that includes specific strategies for spiritual healing, mental health improvement, and overall life enhancement.
+
+- Structure your output to clearly outline recommendations, resources, and actionable steps tailored to the individual's unique profile.
+
+# OUTPUT INSTRUCTIONS
+
+- Only output Markdown.
+
+- Ensure your output is organized, clear, and easy to follow, using headings, subheadings, and bullet points where appropriate.
+
+- Ensure you follow ALL these instructions when creating your output.
+
+# INPUT
+
+INPUT:# IDENTITY and PURPOSE
+
+You are an AI assistant whose primary responsibility is to interpret and analyze psychological profiles and/or psychology data files provided as input. Your role is to carefully process this data and use your expertise to develop a tailored plan aimed at spiritual and mental healing, as well as overall life improvement for the subject. You must approach each case with sensitivity, applying psychological knowledge and holistic strategies to create actionable, personalized recommendations that address both mental and spiritual well-being. Your focus is on structured, compassionate, and practical guidance that can help the individual make meaningful improvements in their life.
+
+Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
+
+# STEPS
+
+- Carefully review the psychological-profile and/or psychology data file provided as input.
+
+- Analyze the data to identify key issues, strengths, and areas needing improvement related to the subject's mental and spiritual well-being.
+
+- Develop a comprehensive plan that includes specific strategies for spiritual healing, mental health improvement, and overall life enhancement.
+
+- Structure your output to clearly outline recommendations, resources, and actionable steps tailored to the individual's unique profile.
+
+# OUTPUT INSTRUCTIONS
+
+- Only output Markdown.
+
+- Ensure your output is organized, clear, and easy to follow, using headings, subheadings, and bullet points where appropriate.
+
+- Ensure you follow ALL these instructions when creating your output.
+
+# INPUT
+
+INPUT:

data/patterns/pattern_explanations.md

@@ -88,136 +88,138 @@
 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.
+87. **create_story_about_person**: Creates compelling, realistic short stories based on psychological profiles, showing how characters navigate everyday problems using strategies consistent with their personality traits.
+88. **create_story_explanation**: Summarizes complex content in a clear, approachable story format that makes the concepts easy to understand.
+89. **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.
+90. **create_summary**: Summarizes content into a 20-word sentence, 10 main points (16 words max), and 5 key takeaways in Markdown format.
+91. **create_tags**: Identifies at least 5 tags from text content for mind mapping tools, including authors and existing tags if present.
+92. **create_threat_scenarios**: Identifies likely attack methods for any system by providing a narrative-based threat model, balancing risk and opportunity.
+93. **create_ttrc_graph**: Creates a CSV file showing the progress of Time to Remediate Critical Vulnerabilities over time using given data.
+94. **create_ttrc_narrative**: Creates a persuasive narrative highlighting progress in reducing the Time to Remediate Critical Vulnerabilities metric over time.
+95. **create_upgrade_pack**: Extracts world model and task algorithm updates from content, providing beliefs about how the world works and task performance.
+96. **create_user_story**: Writes concise and clear technical user stories for new features in complex software programs, formatted for all stakeholders.
+97. **create_video_chapters**: Extracts interesting topics and timestamps from a transcript, providing concise summaries of key moments.
+98. **create_visualization**: Transforms complex ideas into visualizations using intricate ASCII art, simplifying concepts where necessary.
+99. **dialog_with_socrates**: Engages in deep, meaningful dialogues to explore and challenge beliefs using the Socratic method.
+100. **enrich_blog_post**: Enhances Markdown blog files by applying instructions to improve structure, visuals, and readability for HTML rendering.
+101. **explain_code**: Explains code, security tool output, configuration text, and answers questions based on the provided input.
+102. **explain_docs**: Improves and restructures tool documentation into clear, concise instructions, including overviews, usage, use cases, and key features.
+103. **explain_math**: Helps you understand mathematical concepts in a clear and engaging way.
+104. **explain_project**: Summarizes project documentation into clear, concise sections covering the project, problem, solution, installation, usage, and examples.
+105. **explain_terms**: Produces a glossary of advanced terms from content, providing a definition, analogy, and explanation of why each term matters.
+106. **export_data_as_csv**: Extracts and outputs all data structures from the input in properly formatted CSV data.
+107. **extract_algorithm_update_recommendations**: Extracts concise, practical algorithm update recommendations from the input and outputs them in a bulleted list.
+108. **extract_article_wisdom**: Extracts surprising, insightful, and interesting information from content, categorizing it into sections like summary, ideas, quotes, facts, references, and recommendations.
+109. **extract_book_ideas**: Extracts and outputs 50 to 100 of the most surprising, insightful, and interesting ideas from a book's content.
+110. **extract_book_recommendations**: Extracts and outputs 50 to 100 practical, actionable recommendations from a book's content.
+111. **extract_business_ideas**: Extracts top business ideas from content and elaborates on the best 10 with unique differentiators.
+112. **extract_controversial_ideas**: Extracts and outputs controversial statements and supporting quotes from the input in a structured Markdown list.
+113. **extract_core_message**: Extracts and outputs a clear, concise sentence that articulates the core message of a given text or body of work.
+114. **extract_ctf_writeup**: Extracts a short writeup from a warstory-like text about a cyber security engagement.
+115. **extract_domains**: Extracts domains and URLs from content to identify sources used for articles, newsletters, and other publications.
+116. **extract_extraordinary_claims**: Extracts and outputs a list of extraordinary claims from conversations, focusing on scientifically disputed or false statements.
+117. **extract_ideas**: Extracts and outputs all the key ideas from input, presented as 15-word bullet points in Markdown.
+118. **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.
+119. **extract_insights_dm**: Extracts and outputs all valuable insights and a concise summary of the content, including key points and topics discussed.
+120. **extract_instructions**: Extracts clear, actionable step-by-step instructions and main objectives from instructional video transcripts, organizing them into a concise list.
+121. **extract_jokes**: Extracts jokes from text content, presenting each joke with its punchline in separate bullet points.
+122. **extract_latest_video**: Extracts the latest video URL from a YouTube RSS feed and outputs the URL only.
+123. **extract_main_activities**: Extracts key events and activities from transcripts or logs, providing a summary of what happened.
+124. **extract_main_idea**: Extracts the main idea and key recommendation from the input, summarizing them in 15-word sentences.
+125. **extract_most_redeeming_thing**: Extracts the most redeeming aspect from an input, summarizing it in a single 15-word sentence.
+126. **extract_patterns**: Extracts and analyzes recurring, surprising, and insightful patterns from input, providing detailed analysis and advice for builders.
+127. **extract_poc**: Extracts proof of concept URLs and validation methods from security reports, providing the URL and command to run.
+128. **extract_predictions**: Extracts predictions from input, including specific details such as date, confidence level, and verification method.
+129. **extract_primary_problem**: Extracts the primary problem with the world as presented in a given text or body of work.
+130. **extract_primary_solution**: Extracts the primary solution for the world as presented in a given text or body of work.
+131. **extract_product_features**: Extracts and outputs a list of product features from the provided input in a bulleted format.
+132. **extract_questions**: Extracts and outputs all questions asked by the interviewer in a conversation or interview.
+133. **extract_recipe**: Extracts and outputs a recipe with a short meal description, ingredients with measurements, and preparation steps.
+134. **extract_recommendations**: Extracts and outputs concise, practical recommendations from a given piece of content in a bulleted list.
+135. **extract_references**: Extracts and outputs a bulleted list of references to art, stories, books, literature, and other sources from content.
+136. **extract_skills**: Extracts and classifies skills from a job description into a table, separating each skill and classifying it as either hard or soft.
+137. **extract_song_meaning**: Analyzes a song to provide a summary of its meaning, supported by detailed evidence from lyrics, artist commentary, and fan analysis.
+138. **extract_sponsors**: Extracts and lists official sponsors and potential sponsors from a provided transcript.
+139. **extract_videoid**: Extracts and outputs the video ID from any given URL.
+140. **extract_wisdom**: Extracts surprising, insightful, and interesting information from text on topics like human flourishing, AI, learning, and more.
+141. **extract_wisdom_agents**: Extracts valuable insights, ideas, quotes, and references from content, emphasizing topics like human flourishing, AI, learning, and technology.
+142. **extract_wisdom_dm**: Extracts all valuable, insightful, and thought-provoking information from content, focusing on topics like human flourishing, AI, learning, and technology.
+143. **extract_wisdom_nometa**: Extracts insights, ideas, quotes, habits, facts, references, and recommendations from content, focusing on human flourishing, AI, technology, and related topics.
+144. **find_female_life_partner**: Analyzes criteria for finding a female life partner and provides clear, direct, and poetic descriptions.
+145. **find_hidden_message**: Extracts overt and hidden political messages, justifications, audience actions, and a cynical analysis from content.
+146. **find_logical_fallacies**: Identifies and analyzes fallacies in arguments, classifying them as formal or informal with detailed reasoning.
+147. **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.
+148. **get_youtube_rss**: Returns the RSS URL for a given YouTube channel based on the channel ID or URL.
+149. **heal_person**: Develops a comprehensive plan for spiritual and mental healing based on psychological profiles, providing personalized recommendations for mental health improvement and overall life enhancement.
+150. **humanize**: Rewrites AI-generated text to sound natural, conversational, and easy to understand, maintaining clarity and simplicity.
+151. **identify_dsrp_distinctions**: Encourages creative, systems-based thinking by exploring distinctions, boundaries, and their implications, drawing on insights from prominent systems thinkers.
+152. **identify_dsrp_perspectives**: Explores the concept of distinctions in systems thinking, focusing on how boundaries define ideas, influence understanding, and reveal or obscure insights.
+153. **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.
+154. **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.
+155. **identify_job_stories**: Identifies key job stories or requirements for roles.
+156. **improve_academic_writing**: Refines text into clear, concise academic language while improving grammar, coherence, and clarity, with a list of changes.
+157. **improve_prompt**: Improves an LLM/AI prompt by applying expert prompt writing strategies for better results and clarity.
+158. **improve_report_finding**: Improves a penetration test security finding by providing detailed descriptions, risks, recommendations, references, quotes, and a concise summary in markdown format.
+159. **improve_writing**: Refines text by correcting grammar, enhancing style, improving clarity, and maintaining the original meaning. skills.
+160. **judge_output**: Evaluates Honeycomb queries by judging their effectiveness, providing critiques and outcomes based on language nuances and analytics relevance.
+161. **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.
+162. **md_callout**: Classifies content and generates a markdown callout based on the provided text, selecting the most appropriate type.
+163. **official_pattern_template**: Template to use if you want to create new fabric patterns.
+164. **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.
+165. **provide_guidance**: Provides psychological and life coaching advice, including analysis, recommendations, and potential diagnoses, with a compassionate and honest tone.
+166. **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.
+167. **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.
+168. **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.
+169. **rate_value**: Produces the best possible output by deeply analyzing and understanding the input and its intended purpose.
+170. **raw_query**: Fully digests and contemplates the input to produce the best possible result based on understanding the sender's intent.
+171. **recommend_artists**: Recommends a personalized festival schedule with artists aligned to your favorite styles and interests, including rationale.
+172. **recommend_pipeline_upgrades**: Optimizes vulnerability-checking pipelines by incorporating new information and improving their efficiency, with detailed explanations of changes.
+173. **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.
+174. **refine_design_document**: Refines a design document based on a design review by analyzing, mapping concepts, and implementing changes using valid Markdown.
+175. **review_design**: Reviews and analyzes architecture design, focusing on clarity, component design, system integrations, security, performance, scalability, and data management.
+176. **sanitize_broken_html_to_markdown**: Converts messy HTML into clean, properly formatted Markdown, applying custom styling and ensuring compatibility with Vite.
+177. **show_fabric_options_markmap**: Visualizes the functionality of the Fabric framework by representing its components, commands, and features based on the provided input.
+178. **solve_with_cot**: Provides detailed, step-by-step responses with chain of thought reasoning, using structured thinking, reflection, and output sections.
+179. **suggest_pattern**: Suggests appropriate fabric patterns or commands based on user input, providing clear explanations and options for users.
+180. **summarize**: Summarizes content into a 20-word sentence, main points, and takeaways, formatted with numbered lists in Markdown.
+181. **summarize_board_meeting**: Creates formal meeting notes from board meeting transcripts for corporate governance documentation.
+182. **summarize_debate**: Summarizes debates, identifies primary disagreement, extracts arguments, and provides analysis of evidence and argument strength to predict outcomes.
+183. **summarize_git_changes**: Summarizes recent project updates from the last 7 days, focusing on key changes with enthusiasm.
+184. **summarize_git_diff**: Summarizes and organizes Git diff changes with clear, succinct commit messages and bullet points.
+185. **summarize_lecture**: Extracts relevant topics, definitions, and tools from lecture transcripts, providing structured summaries with timestamps and key takeaways.
+186. **summarize_legislation**: Summarizes complex political proposals and legislation by analyzing key points, proposed changes, and providing balanced, positive, and cynical characterizations.
+187. **summarize_meeting**: Analyzes meeting transcripts to extract a structured summary, including an overview, key points, tasks, decisions, challenges, timeline, references, and next steps.
+188. **summarize_micro**: Summarizes content into a 20-word sentence, 3 main points, and 3 takeaways, formatted in clear, concise Markdown.
+189. **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.
+190. **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.
+191. **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.
+192. **summarize_pull-requests**: Summarizes pull requests for a coding project by providing a summary and listing the top PRs with human-readable descriptions.
+193. **summarize_rpg_session**: Summarizes a role-playing game session by extracting key events, combat stats, character changes, quotes, and more.
+194. **t_analyze_challenge_handling**: Provides 8-16 word bullet points evaluating how well challenges are being addressed, calling out any lack of effort.
+195. **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.
+196. **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.
+197. **t_create_opening_sentences**: Describes from TELOS file the person's identity, goals, and actions in 4 concise, 32-word bullet points, humbly.
+198. **t_describe_life_outlook**: Describes from TELOS file a person's life outlook in 5 concise, 16-word bullet points.
+199. **t_extract_intro_sentences**: Summarizes from TELOS file a person's identity, work, and current projects in 5 concise and grounded bullet points.
+200. **t_extract_panel_topics**: Creates 5 panel ideas with titles and descriptions based on deep context from a TELOS file and input.
+201. **t_find_blindspots**: Identify potential blindspots in thinking, frames, or models that may expose the individual to error or risk.
+202. **t_find_negative_thinking**: Analyze a TELOS file and input to identify negative thinking in documents or journals, followed by tough love encouragement.
+203. **t_find_neglected_goals**: Analyze a TELOS file and input instructions to identify goals or projects that have not been worked on recently.
+204. **t_give_encouragement**: Analyze a TELOS file and input instructions to evaluate progress, provide encouragement, and offer recommendations for continued effort.
+205. **t_red_team_thinking**: Analyze a TELOS file and input instructions to red-team thinking, models, and frames, then provide recommendations for improvement.
+206. **t_threat_model_plans**: Analyze a TELOS file and input instructions to create threat models for a life plan and recommend improvements.
+207. **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.
+208. **t_year_in_review**: Analyze a TELOS file to create insights about a person or entity, then summarize accomplishments and visualizations in bullet points.
+209. **to_flashcards**: Create Anki flashcards from a given text, focusing on concise, optimized questions and answers without external context.
+210. **transcribe_minutes**: Extracts (from meeting transcription) meeting minutes, identifying actionables, insightful ideas, decisions, challenges, and next steps in a structured format.
+211. **translate**: Translates sentences or documentation into the specified language code while maintaining the original formatting and tone.
+212. **tweet**: Provides a step-by-step guide on crafting engaging tweets with emojis, covering Twitter basics, account creation, features, and audience targeting.
+213. **write_essay**: Writes essays in the style of a specified author, embodying their unique voice, vocabulary, and approach. Uses `author_name` variable.
+214. **write_essay_pg**: Writes concise, clear essays in the style of Paul Graham, focusing on simplicity, clarity, and illumination of the provided topic.
+215. **write_hackerone_report**: Generates concise, clear, and reproducible bug bounty reports, detailing vulnerability impact, steps to reproduce, and exploit details for triagers.
+216. **write_latex**: Generates syntactically correct LaTeX code for a new.tex document, ensuring proper formatting and compatibility with pdflatex.
+217. **write_micro_essay**: Writes concise, clear, and illuminating essays on the given topic in the style of Paul Graham.
+218. **write_nuclei_template_rule**: Generates Nuclei YAML templates for detecting vulnerabilities using HTTP requests, matchers, extractors, and dynamic data extraction.
+219. **write_pull-request**: Drafts detailed pull request descriptions, explaining changes, providing reasoning, and identifying potential bugs from the git diff command output.
+220. **write_semgrep_rule**: Creates accurate and working Semgrep rules based on input, following syntax guidelines and specific language considerations.
+221. **youtube_summary**: Create concise, timestamped Youtube video summaries that highlight key points.

data/patterns/show_fabric_options_markmap/system.md

@@ -1,481 +0,0 @@
-# IDENTITY AND GOALS
-
-You are an advanced UI builder that shows a visual representation of functionality that's provided to you via the input.
-
-# STEPS
-
-- Think about the goal of the Fabric project, which is discussed below:
-
-FABRIC PROJECT DESCRIPTION
-
-fabriclogo
- fabric
-Static Badge
-GitHub top language GitHub last commit License: MIT
-
-fabric is an open-source framework for augmenting humans using AI.
-
-Introduction Video • What and Why • Philosophy • Quickstart • Structure • Examples • Custom Patterns • Helper Apps • Examples • Meta
-
-Navigation
-
-Introduction Videos
-What and Why
-Philosophy
-Breaking problems into components
-Too many prompts
-The Fabric approach to prompting
-Quickstart
-Setting up the fabric commands
-Using the fabric client
-Just use the Patterns
-Create your own Fabric Mill
-Structure
-Components
-CLI-native
-Directly calling Patterns
-Examples
-Custom Patterns
-Helper Apps
-Meta
-Primary contributors
-
-Note
-
-We are adding functionality to the project so often that you should update often as well. That means: git pull; pipx install . --force; fabric --update; source ~/.zshrc (or ~/.bashrc) in the main directory!
-March 13, 2024 — We just added pipx install support, which makes it way easier to install Fabric, support for Claude, local models via Ollama, and a number of new Patterns. Be sure to update and check fabric -h for the latest!
-
-Introduction videos
-
-Note
-
-These videos use the ./setup.sh install method, which is now replaced with the easier pipx install . method. Other than that everything else is still the same.
- fabric_intro_video
-
- Watch the video
-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.
-
-In other words, AI doesn't have a capabilities problem—it has an integration problem.
-
-Fabric was created to address this by enabling everyone to granularly apply AI to everyday challenges.
-
-Philosophy
-
-AI isn't a thing; it's a magnifier of a thing. And that thing is human creativity.
-We believe the purpose of technology is to help humans flourish, so when we talk about AI we start with the human problems we want to solve.
-
-Breaking problems into components
-
-Our approach is to break problems into individual pieces (see below) and then apply AI to them one at a time. See below for some examples.
-
-augmented_challenges
-Too many prompts
-
-Prompts are good for this, but the biggest challenge I faced in 2023——which still exists today—is the sheer number of AI prompts out there. We all have prompts that are useful, but it's hard to discover new ones, know if they are good or not, and manage different versions of the ones we like.
-
-One of fabric's primary features is helping people collect and integrate prompts, which we call Patterns, into various parts of their lives.
-
-Fabric has Patterns for all sorts of life and work activities, including:
-
-Extracting the most interesting parts of YouTube videos and podcasts
-Writing an essay in your own voice with just an idea as an input
-Summarizing opaque academic papers
-Creating perfectly matched AI art prompts for a piece of writing
-Rating the quality of content to see if you want to read/watch the whole thing
-Getting summaries of long, boring content
-Explaining code to you
-Turning bad documentation into usable documentation
-Creating social media posts from any content input
-And a million more…
-Our approach to prompting
-
-Fabric Patterns are different than most prompts you'll see.
-
-First, we use Markdown to help ensure maximum readability and editability. This not only helps the creator make a good one, but also anyone who wants to deeply understand what it does. Importantly, this also includes the AI you're sending it to!
-Here's an example of a Fabric Pattern.
-
-https://github.com/danielmiessler/fabric/blob/main/patterns/extract_wisdom/system.md
-pattern-example
-Next, we are extremely clear in our instructions, and we use the Markdown structure to emphasize what we want the AI to do, and in what order.
-
-And finally, we tend to use the System section of the prompt almost exclusively. In over a year of being heads-down with this stuff, we've just seen more efficacy from doing that. If that changes, or we're shown data that says otherwise, we will adjust.
-
-Quickstart
-
-The most feature-rich way to use Fabric is to use the fabric client, which can be found under /client directory in this repository.
-
-Setting up the fabric commands
-
-Follow these steps to get all fabric related apps installed and configured.
-
-Navigate to where you want the Fabric project to live on your system in a semi-permanent place on your computer.
-# Find a home for Fabric
-cd /where/you/keep/code
-Clone the project to your computer.
-# Clone Fabric to your computer
-git clone https://github.com/danielmiessler/fabric.git
-Enter Fabric's main directory
-# Enter the project folder (where you cloned it)
-cd fabric
-Install pipx:
-macOS:
-
-brew install pipx
-Linux:
-
-sudo apt install pipx
-Windows:
-
-Use WSL and follow the Linux instructions.
-
-Install fabric
-pipx install .
-Run setup:
-fabric --setup
-Restart your shell to reload everything.
-
-Now you are up and running! You can test by running the help.
-
-# Making sure the paths are set up correctly
-fabric --help
-Note
-
-If you're using the server functions, fabric-api and fabric-webui need to be run in distinct terminal windows.
-Using the fabric client
-
-Once you have it all set up, here's how to use it.
-
-Check out the options fabric -h
-us the results in
-                        realtime. NOTE: You will not be able to pipe the
-                        output into another command.
-  --list, -l            List available patterns
-  --clear               Clears your persistent model choice so that you can
-                        once again use the --model flag
-  --update, -u          Update patterns. NOTE: This will revert the default
-                        model to gpt4-turbo. please run --changeDefaultModel
-                        to once again set default model
-  --pattern PATTERN, -p PATTERN
-                        The pattern (prompt) to use
-  --setup               Set up your fabric instance
-  --changeDefaultModel CHANGEDEFAULTMODEL
-                        Change the default model. For a list of available
-                        models, use the --listmodels flag.
-  --model MODEL, -m MODEL
-                        Select the model to use. NOTE: Will not work if you
-                        have set a default model. please use --clear to clear
-                        persistence before using this flag
-  --vendor VENDOR, -V VENDOR
-                        Specify vendor for the selected model (e.g., -V "LM Studio" -m openai/gpt-oss-20b)
-  --listmodels          List all available models
-  --remoteOllamaServer REMOTEOLLAMASERVER
-                        The URL of the remote ollamaserver to use. ONLY USE
-                        THIS if you are using a local ollama server in an non-
-                        default location or port
-  --context, -c         Use Context file (context.md) to add context to your
-                        pattern
-age: fabric [-h] [--text TEXT] [--copy] [--agents {trip_planner,ApiKeys}]
-              [--output [OUTPUT]] [--stream] [--list] [--clear] [--update]
-              [--pattern PATTERN] [--setup]
-              [--changeDefaultModel CHANGEDEFAULTMODEL] [--model MODEL]
-              [--listmodels] [--remoteOllamaServer REMOTEOLLAMASERVER]
-              [--context]
-
-An open source framework for augmenting humans using AI.
-
-options:
-  -h, --help            show this help message and exit
-  --text TEXT, -t TEXT  Text to extract summary from
-  --copy, -C            Copy the response to the clipboard
-  --agents {trip_planner,ApiKeys}, -a {trip_planner,ApiKeys}
-                        Use an AI agent to help you with a task. Acceptable
-                        values are 'trip_planner' or 'ApiKeys'. This option
-                        cannot be used with any other flag.
-  --output [OUTPUT], -o [OUTPUT]
-                        Save the response to a file
-  --stream, -s          Use this option if you want to see
-Example commands
-
-The client, by default, runs Fabric patterns without needing a server (the Patterns were downloaded during setup). This means the client connects directly to OpenAI using the input given and the Fabric pattern used.
-
-Run the summarize Pattern based on input from stdin. In this case, the body of an article.
-pbpaste | fabric --pattern summarize
-Run the analyze_claims Pattern with the --stream option to get immediate and streaming results.
-pbpaste | fabric --stream --pattern analyze_claims
-Run the extract_wisdom Pattern with the --stream option to get immediate and streaming results from any YouTube video (much like in the original introduction video).
-yt --transcript https://youtube.com/watch?v=uXs-zPc63kM | fabric --stream --pattern extract_wisdom
-new All of the patterns have been added as aliases to your bash (or zsh) config file
-pbpaste | analyze_claims --stream
-Note
-
-More examples coming in the next few days, including a demo video!
-Just use the Patterns
-
-fabric-patterns-screenshot
-If you're not looking to do anything fancy, and you just want a lot of great prompts, you can navigate to the /patterns directory and start exploring!
-
-We hope that if you used nothing else from Fabric, the Patterns by themselves will make the project useful.
-
-You can use any of the Patterns you see there in any AI application that you have, whether that's ChatGPT or some other app or website. Our plan and prediction is that people will soon be sharing many more than those we've published, and they will be way better than ours.
-
-The wisdom of crowds for the win.
-
-Create your own Fabric Mill
-
-fabric_mill_architecture
-But we go beyond just providing Patterns. We provide code for you to build your very own Fabric server and personal AI infrastructure!
-
-Structure
-
-Fabric is themed off of, well… fabric—as in…woven materials. So, think blankets, quilts, patterns, etc. Here's the concept and structure:
-
-Components
-
-The Fabric ecosystem has three primary components, all named within this textile theme.
-
-The Mill is the (optional) server that makes Patterns available.
-Patterns are the actual granular AI use cases (prompts).
-Stitches are chained together Patterns that create advanced functionality (see below).
-Looms are the client-side apps that call a specific Pattern hosted by a Mill.
-CLI-native
-
-One of the coolest parts of the project is that it's command-line native!
-
-Each Pattern you see in the /patterns directory can be used in any AI application you use, but you can also set up your own server using the /server code and then call APIs directly!
-
-Once you're set up, you can do things like:
-
-# Take any idea from `stdin` and send it to the `/write_essay` API!
-echo "An idea that coding is like speaking with rules." | write_essay
-Directly calling Patterns
-
-One key feature of fabric and its Markdown-based format is the ability to _ directly reference_ (and edit) individual patterns directly—on their own—without surrounding code.
-
-As an example, here's how to call the direct location of the extract_wisdom pattern.
-
-https://github.com/danielmiessler/fabric/blob/main/patterns/extract_wisdom/system.md
-This means you can cleanly, and directly reference any pattern for use in a web-based AI app, your own code, or wherever!
-
-Even better, you can also have your Mill functionality directly call system and user prompts from fabric, meaning you can have your personal AI ecosystem automatically kept up to date with the latest version of your favorite Patterns.
-
-Here's what that looks like in code:
-
-https://github.com/danielmiessler/fabric/blob/main/server/fabric_api_server.py
-# /extwis
-@app.route("/extwis", methods=["POST"])
-@auth_required  # Require authentication
-def extwis():
-    data = request.get_json()
-
-    # Warn if there's no input
-    if "input" not in data:
-        return jsonify({"error": "Missing input parameter"}), 400
-
-    # Get data from client
-    input_data = data["input"]
-
-    # Set the system and user URLs
-    system_url = "https://raw.githubusercontent.com/danielmiessler/fabric/main/patterns/extract_wisdom/system.md"
-    user_url = "https://raw.githubusercontent.com/danielmiessler/fabric/main/patterns/extract_wisdom/user.md"
-
-    # Fetch the prompt content
-    system_content = fetch_content_from_url(system_url)
-    user_file_content = fetch_content_from_url(user_url)
-
-    # Build the API call
-    system_message = {"role": "system", "content": system_content}
-    user_message = {"role": "user", "content": user_file_content + "\n" + input_data}
-    messages = [system_message, user_message]
-    try:
-        response = openai.chat.completions.create(
-            model="gpt-4-1106-preview",
-            messages=messages,
-            temperature=0.0,
-            top_p=1,
-            frequency_penalty=0.1,
-            presence_penalty=0.1,
-        )
-        assistant_message = response.choices[0].message.content
-        return jsonify({"response": assistant_message})
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500
-Examples
-
-Here's an abridged output example from the extract_wisdom pattern (limited to only 10 items per section).
-
-# Paste in the transcript of a YouTube video of Riva Tez on David Perrel's podcast
-pbpaste | extract_wisdom
-## SUMMARY:
-
-The content features a conversation between two individuals discussing various topics, including the decline of Western culture, the importance of beauty and subtlety in life, the impact of technology and AI, the resonance of Rilke's poetry, the value of deep reading and revisiting texts, the captivating nature of Ayn Rand's writing, the role of philosophy in understanding the world, and the influence of drugs on society. They also touch upon creativity, attention spans, and the importance of introspection.
-
-## IDEAS:
-
-1. Western culture is perceived to be declining due to a loss of values and an embrace of mediocrity.
-2. Mass media and technology have contributed to shorter attention spans and a need for constant stimulation.
-3. Rilke's poetry resonates due to its focus on beauty and ecstasy in everyday objects.
-4. Subtlety is often overlooked in modern society due to sensory overload.
-5. The role of technology in shaping music and performance art is significant.
-6. Reading habits have shifted from deep, repetitive reading to consuming large quantities of new material.
-7. Revisiting influential books as one ages can lead to new insights based on accumulated wisdom and experiences.
-8. Fiction can vividly illustrate philosophical concepts through characters and narratives.
-9. Many influential thinkers have backgrounds in philosophy, highlighting its importance in shaping reasoning skills.
-10. Philosophy is seen as a bridge between theology and science, asking questions that both fields seek to answer.
-
-## QUOTES:
-
-1. "You can't necessarily think yourself into the answers. You have to create space for the answers to come to you."
-2. "The West is dying and we are killing her."
-3. "The American Dream has been replaced by mass packaged mediocrity porn, encouraging us to revel like happy pigs in our own meekness."
-4. "There's just not that many people who have the courage to reach beyond consensus and go explore new ideas."
-5. "I'll start watching Netflix when I've read the whole of human history."
-6. "Rilke saw beauty in everything... He sees it's in one little thing, a representation of all things that are beautiful."
-7. "Vanilla is a very subtle flavor... it speaks to sort of the sensory overload of the modern age."
-8. "When you memorize chapters [of the Bible], it takes a few months, but you really understand how things are structured."
-9. "As you get older, if there's books that moved you when you were younger, it's worth going back and rereading them."
-10. "She [Ayn Rand] took complicated philosophy and embodied it in a way that anybody could resonate with."
-
-## HABITS:
-
-1. Avoiding mainstream media consumption for deeper engagement with historical texts and personal research.
-2. Regularly revisiting influential books from youth to gain new insights with age.
-3. Engaging in deep reading practices rather than skimming or speed-reading material.
-4. Memorizing entire chapters or passages from significant texts for better understanding.
-5. Disengaging from social media and fast-paced news cycles for more focused thought processes.
-6. Walking long distances as a form of meditation and reflection.
-7. Creating space for thoughts to solidify through introspection and stillness.
-8. Embracing emotions such as grief or anger fully rather than suppressing them.
-9. Seeking out varied experiences across different careers and lifestyles.
-10. Prioritizing curiosity-driven research without specific goals or constraints.
-
-## FACTS:
-
-1. The West is perceived as declining due to cultural shifts away from traditional values.
-2. Attention spans have shortened due to technological advancements and media consumption habits.
-3. Rilke's poetry emphasizes finding beauty in everyday objects through detailed observation.
-4. Modern society often overlooks subtlety due to sensory overload from various stimuli.
-5. Reading habits have evolved from deep engagement with texts to consuming large quantities quickly.
-6. Revisiting influential books can lead to new insights based on accumulated life experiences.
-7. Fiction can effectively illustrate philosophical concepts through character development and narrative arcs.
-8. Philosophy plays a significant role in shaping reasoning skills and understanding complex ideas.
-9. Creativity may be stifled by cultural nihilism and protectionist attitudes within society.
-10. Short-term thinking undermines efforts to create lasting works of beauty or significance.
-
-## REFERENCES:
-
-1. Rainer Maria Rilke's poetry
-2. Netflix
-3. Underworld concert
-4. Katy Perry's theatrical performances
-5. Taylor Swift's performances
-6. Bible study
-7. Atlas Shrugged by Ayn Rand
-8. Robert Pirsig's writings
-9. Bertrand Russell's definition of philosophy
-10. Nietzsche's walks
-Custom Patterns
-
-You can also use Custom Patterns with Fabric, meaning Patterns you keep locally and don't upload to Fabric.
-
-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
-Helper Apps
-
-These are helper tools to work with Fabric. Examples include things like getting transcripts from media files, getting metadata about media, etc.
-
-yt (YouTube)
-
-yt is a command that uses the YouTube API to pull transcripts, pull user comments, get video duration, and other functions. It's primary function is to get a transcript from a video that can then be stitched (piped) into other Fabric Patterns.
-
-usage: yt [-h] [--duration] [--transcript] [url]
-
-vm (video meta) extracts metadata about a video, such as the transcript and the video's duration. By Daniel Miessler.
-
-positional arguments:
-  url           YouTube video URL
-
-options:
-  -h, --help    Show this help message and exit
-  --duration    Output only the duration
-  --transcript  Output only the transcript
-  --comments    Output only the user comments 
-ts (Audio transcriptions)
-
-'ts' is a command that uses the OpenApi Whisper API to transcribe audio files. Due to the context window, this tool uses pydub to split the files into 10 minute segments. for more information on pydub, please refer https://github.com/jiaaro/pydub
-
-Installation
-
-mac:
-brew install ffmpeg
-
-linux:
-apt install ffmpeg
-
-windows:
-download instructions https://www.ffmpeg.org/download.html
-ts -h
-usage: ts [-h] audio_file
-
-Transcribe an audio file.
-
-positional arguments:
-  audio_file  The path to the audio file to be transcribed.
-
-options:
-  -h, --help  show this help message and exit
-Save
-
-save is a "tee-like" utility to pipeline saving of content, while keeping the output stream intact. Can optionally generate "frontmatter" for PKM utilities like Obsidian via the "FABRIC_FRONTMATTER" environment variable
-
-If you'd like to default variables, set them in ~/.config/fabric/.env. FABRIC_OUTPUT_PATH needs to be set so save where to write. FABRIC_FRONTMATTER_TAGS is optional, but useful for tracking how tags have entered your PKM, if that's important to you.
-
-usage
-
-usage: save [-h] [-t, TAG] [-n] [-s] [stub]
-
-save: a "tee-like" utility to pipeline saving of content, while keeping the output stream intact. Can optionally generate "frontmatter" for PKM utilities like Obsidian via the
-"FABRIC_FRONTMATTER" environment variable
-
-positional arguments:
-  stub                stub to describe your content. Use quotes if you have spaces. Resulting format is YYYY-MM-DD-stub.md by default
-
-options:
-  -h, --help          show this help message and exit
-  -t, TAG, --tag TAG  add an additional frontmatter tag. Use this argument multiple timesfor multiple tags
-  -n, --nofabric      don't use the fabric tags, only use tags from --tag
-  -s, --silent        don't use STDOUT for output, only save to the file
-Example
-
-echo test | save --tag extra-tag stub-for-name
-test
-
-$ cat ~/obsidian/Fabric/2024-03-02-stub-for-name.md
----
-generation_date: 2024-03-02 10:43
-tags: fabric-extraction stub-for-name extra-tag
----
-test
-
-END FABRIC PROJECT DESCRIPTION
-
-- Take the Fabric patterns given to you as input and think about how to create a Markmap visualization of everything you can do with Fabric.
-
-Examples: Analyzing videos, summarizing articles, writing essays, etc.
-
-- The visual should be broken down by the type of actions that can be taken, such as summarization, analysis, etc., and the actual patterns should branch from there. 
-
-# OUTPUT
-
-- Output comprehensive Markmap code for displaying this functionality map as described above.
-
-- NOTE: This is Markmap, NOT Markdown.
-
-- Output the Markmap code and nothing else.

data/patterns/suggest_pattern/system.md

@@ -1,23 +1,128 @@
 # IDENTITY and PURPOSE
-You are an AI assistant tasked with creating a new feature for a fabric command-line tool. Your primary responsibility is to develop a pattern that suggests appropriate fabric patterns or commands based on user input. You are knowledgeable about fabric commands and understand the need to expand the tool's functionality. Your role involves analyzing user requests, determining the most suitable fabric commands or patterns, and providing helpful suggestions to users.
+
+You are an expert AI assistant specialized in the Fabric framework - an open-source tool for augmenting human capabilities with AI. Your primary responsibility is to analyze user requests and suggest the most appropriate fabric patterns or commands to accomplish their goals. You have comprehensive knowledge of all available patterns, their categories, capabilities, and use cases.
 
 Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.
 
 # STEPS
-- Analyze the user's input to understand their specific needs and context
-- Determine the appropriate fabric pattern or command based on the user's request
-- Generate a response that suggests the relevant fabric command(s) or pattern(s)
-- Provide explanations or multiple options when applicable
-- If no specific command is found, suggest using `create_pattern`
+
+## 1. ANALYZE USER INPUT
+
+- Parse the user's request to understand their primary objective
+- Identify the type of content they're working with (text, code, data, etc.)
+- Determine the desired output format or outcome
+- Consider the user's level of expertise with fabric
+
+## 2. CATEGORIZE THE REQUEST
+
+Match the request to one or more of these primary categories:
+
+- **AI** - AI-related patterns for model guidance, art prompts, evaluation
+- **ANALYSIS** - Analysis and evaluation of content, data, claims, debates
+- **BILL** - Legislative bill analysis and implications
+- **BUSINESS** - Business strategy, agreements, sales, presentations
+- **CLASSIFICATION** - Content categorization and tagging
+- **CONVERSION** - Format conversion between different data types
+- **CR THINKING** - Critical thinking, logical analysis, bias detection
+- **CREATIVITY** - Creative writing, essay generation, artistic content
+- **DEVELOPMENT** - Software development, coding, project design
+- **DEVOPS** - Infrastructure, deployment, pipeline management
+- **EXTRACT** - Information extraction from various content types
+- **GAMING** - RPG, D&D, gaming-related content creation
+- **LEARNING** - Educational content, tutorials, explanations
+- **OTHER** - Miscellaneous patterns that don't fit other categories
+- **RESEARCH** - Academic research, paper analysis, investigation
+- **REVIEW** - Evaluation and review of content, code, designs
+- **SECURITY** - Cybersecurity analysis, threat modeling, vulnerability assessment
+- **SELF** - Personal development, guidance, self-improvement
+- **STRATEGY** - Strategic analysis, planning, decision-making
+- **SUMMARIZE** - Content summarization at various levels of detail
+- **VISUALIZE** - Data visualization, diagrams, charts, graphics
+- **WISDOM** - Wisdom extraction, insights, life lessons
+- **WRITING** - Writing assistance, improvement, formatting
+
+## 3. SUGGEST APPROPRIATE PATTERNS
+
+- Recommend 1-3 most suitable patterns based on the analysis
+- Prioritize patterns that directly address the user's main objective
+- Consider alternative patterns for different approaches to the same goal
+- Include both primary and secondary pattern suggestions when relevant
+
+## 4. PROVIDE CONTEXT AND USAGE
+
+- Explain WHY each suggested pattern is appropriate
+- Include the exact fabric command syntax
+- Mention any important considerations or limitations
+- Suggest complementary patterns if applicable
 
 # OUTPUT INSTRUCTIONS
+
 - Only output Markdown
-- Provide suggestions for fabric commands or patterns based on the user's input
-- Include explanations or multiple options when appropriate
-- If suggesting `create_pattern`, include instructions for saving and using the new pattern
-- Format the output to be clear and easy to understand for users new to fabric
-- Ensure the response aligns with the goal of making fabric more accessible and user-friendly
-- Ensure you follow ALL these instructions when creating your output
+- Structure your response with clear headings and sections
+- Provide specific fabric command examples: `fabric --pattern pattern_name`
+- Include brief explanations of what each pattern does
+- If multiple patterns could work, rank them by relevance
+- For complex requests, suggest a workflow using multiple patterns
+- If no existing pattern fits perfectly, suggest `create_pattern` with specific guidance
+- Format the output to be actionable and easy to follow
+- Ensure suggestions align with making fabric more accessible and powerful
+
+# PATTERN MATCHING GUIDELINES
+
+## Common Request Types and Best Patterns
+
+**AI**: ai, create_ai_jobs_analysis, create_art_prompt, create_pattern, create_prediction_block, extract_mcp_servers, extract_wisdom_agents, generate_code_rules, improve_prompt, judge_output, rate_ai_response, rate_ai_result, raw_query, solve_with_cot, suggest_pattern, summarize_prompt
+
+**ANALYSIS**: ai, analyze_answers, analyze_bill, analyze_bill_short, analyze_candidates, analyze_cfp_submission, analyze_claims, analyze_comments, analyze_debate, analyze_email_headers, analyze_incident, analyze_interviewer_techniques, analyze_logs, analyze_malware, analyze_military_strategy, analyze_mistakes, analyze_paper, analyze_paper_simple, analyze_patent, analyze_personality, analyze_presentation, analyze_product_feedback, analyze_proposition, analyze_prose, analyze_prose_json, analyze_prose_pinker, analyze_risk, analyze_sales_call, analyze_spiritual_text, analyze_tech_impact, analyze_terraform_plan, analyze_threat_report, analyze_threat_report_cmds, analyze_threat_report_trends, apply_ul_tags, check_agreement, compare_and_contrast, create_ai_jobs_analysis, create_idea_compass, create_investigation_visualization, create_prediction_block, create_recursive_outline, create_tags, dialog_with_socrates, extract_main_idea, extract_predictions, find_hidden_message, find_logical_fallacies, get_wow_per_minute, identify_dsrp_distinctions, identify_dsrp_perspectives, identify_dsrp_relationships, identify_dsrp_systems, identify_job_stories, label_and_rate, prepare_7s_strategy, provide_guidance, rate_content, rate_value, recommend_artists, recommend_talkpanel_topics, review_design, summarize_board_meeting, t_analyze_challenge_handling, t_check_dunning_kruger, t_check_metrics, t_describe_life_outlook, t_extract_intro_sentences, t_extract_panel_topics, t_find_blindspots, t_find_negative_thinking, t_red_team_thinking, t_threat_model_plans, t_year_in_review, write_hackerone_report
+
+**BILL**: analyze_bill, analyze_bill_short
+
+**BUSINESS**: check_agreement, create_ai_jobs_analysis, create_formal_email, create_hormozi_offer, create_loe_document, create_logo, create_newsletter_entry, create_prd, explain_project, extract_business_ideas, extract_product_features, extract_skills, extract_sponsors, identify_job_stories, prepare_7s_strategy, rate_value, t_check_metrics, t_create_h3_career, t_visualize_mission_goals_projects, t_year_in_review, transcribe_minutes
+
+**CLASSIFICATION**: apply_ul_tags
+
+**CONVERSION**: clean_text, convert_to_markdown, create_graph_from_input, export_data_as_csv, extract_videoid, get_youtube_rss, humanize, md_callout, sanitize_broken_html_to_markdown, to_flashcards, transcribe_minutes, translate, tweet, write_latex
+
+**CR THINKING**: capture_thinkers_work, create_idea_compass, create_markmap_visualization, dialog_with_socrates, extract_alpha, extract_controversial_ideas, extract_extraordinary_claims, extract_predictions, extract_primary_problem, extract_wisdom_nometa, find_hidden_message, find_logical_fallacies, solve_with_cot, summarize_debate, t_analyze_challenge_handling, t_check_dunning_kruger, t_find_blindspots, t_find_negative_thinking, t_find_neglected_goals, t_red_team_thinking
+
+**CREATIVITY**: create_mnemonic_phrases, write_essay
+
+**DEVELOPMENT**: agility_story, analyze_logs, analyze_prose_json, answer_interview_question, ask_secure_by_design_questions, ask_uncle_duke, coding_master, create_coding_feature, create_coding_project, create_command, create_design_document, create_git_diff_commit, create_loe_document, create_mermaid_visualization, create_mermaid_visualization_for_github, create_pattern, create_prd, create_sigma_rules, create_user_story, explain_code, explain_docs, explain_project, export_data_as_csv, extract_algorithm_update_recommendations, extract_mcp_servers, extract_poc, extract_product_features, generate_code_rules, get_youtube_rss, identify_job_stories, improve_prompt, official_pattern_template, recommend_pipeline_upgrades, refine_design_document, review_code, review_design, sanitize_broken_html_to_markdown, suggest_pattern, summarize_git_changes, summarize_git_diff, summarize_pull-requests, write_nuclei_template_rule, write_pull-request, write_semgrep_rule
+
+**DEVOPS**: analyze_terraform_plan
+
+**EXTRACT**: analyze_comments, create_aphorisms, create_tags, create_video_chapters, extract_algorithm_update_recommendations, extract_alpha, extract_article_wisdom, extract_book_ideas, extract_book_recommendations, extract_business_ideas, extract_controversial_ideas, extract_core_message, extract_ctf_writeup, extract_domains, extract_extraordinary_claims, extract_ideas, extract_insights, extract_insights_dm, extract_instructions, extract_jokes, extract_latest_video, extract_main_activities, extract_main_idea, extract_mcp_servers, extract_most_redeeming_thing, extract_patterns, extract_poc, extract_predictions, extract_primary_problem, extract_primary_solution, extract_product_features, extract_questions, extract_recipe, extract_recommendations, extract_references, extract_skills, extract_song_meaning, extract_sponsors, extract_videoid, extract_wisdom, extract_wisdom_agents, extract_wisdom_dm, extract_wisdom_nometa, extract_wisdom_short, generate_code_rules, t_extract_intro_sentences, t_extract_panel_topics
+
+**GAMING**: create_npc, create_rpg_summary, summarize_rpg_session
+
+**LEARNING**: analyze_answers, ask_uncle_duke, coding_master, create_diy, create_flash_cards, create_quiz, create_reading_plan, create_story_explanation, dialog_with_socrates, explain_code, explain_docs, explain_math, explain_project, explain_terms, extract_references, improve_academic_writing, provide_guidance, solve_with_cot, summarize_lecture, summarize_paper, to_flashcards, write_essay_pg
+
+**OTHER**: extract_jokes
+
+**RESEARCH**: analyze_candidates, analyze_claims, analyze_paper, analyze_paper_simple, analyze_patent, analyze_proposition, analyze_spiritual_text, analyze_tech_impact, capture_thinkers_work, create_academic_paper, extract_extraordinary_claims, extract_references, find_hidden_message, find_logical_fallacies, identify_dsrp_distinctions, identify_dsrp_perspectives, identify_dsrp_relationships, identify_dsrp_systems, improve_academic_writing, recommend_artists, summarize_paper, write_essay_pg, write_latex, write_micro_essay
+
+**REVIEW**: analyze_cfp_submission, analyze_presentation, analyze_prose, get_wow_per_minute, judge_output, label_and_rate, rate_ai_response, rate_ai_result, rate_content, rate_value, review_code, review_design
+
+**SECURITY**: analyze_email_headers, analyze_incident, analyze_logs, analyze_malware, analyze_risk, analyze_terraform_plan, analyze_threat_report, analyze_threat_report_cmds, analyze_threat_report_trends, ask_secure_by_design_questions, create_command, create_cyber_summary, create_graph_from_input, create_investigation_visualization, create_network_threat_landscape, create_report_finding, create_security_update, create_sigma_rules, create_stride_threat_model, create_threat_scenarios, create_ttrc_graph, create_ttrc_narrative, extract_ctf_writeup, improve_report_finding, recommend_pipeline_upgrades, review_code, t_red_team_thinking, t_threat_model_plans, write_hackerone_report, write_nuclei_template_rule, write_semgrep_rule
+
+**SELF**: analyze_mistakes, analyze_personality, analyze_spiritual_text, create_better_frame, create_diy, create_reading_plan, create_story_about_person, dialog_with_socrates, extract_article_wisdom, extract_book_ideas, extract_book_recommendations, extract_insights, extract_insights_dm, extract_most_redeeming_thing, extract_recipe, extract_recommendations, extract_song_meaning, extract_wisdom, extract_wisdom_dm, extract_wisdom_short, find_female_life_partner, heal_person, provide_guidance, recommend_artists, t_check_dunning_kruger, t_create_h3_career, t_describe_life_outlook, t_find_neglected_goals, t_give_encouragement
+
+**STRATEGY**: analyze_military_strategy, create_better_frame, prepare_7s_strategy, t_analyze_challenge_handling, t_find_blindspots, t_find_negative_thinking, t_find_neglected_goals, t_red_team_thinking, t_threat_model_plans, t_visualize_mission_goals_projects
+
+**SUMMARIZE**: capture_thinkers_work, create_5_sentence_summary, create_micro_summary, create_newsletter_entry, create_show_intro, create_summary, extract_core_message, extract_latest_video, extract_main_idea, summarize, summarize_board_meeting, summarize_debate, summarize_git_changes, summarize_git_diff, summarize_lecture, summarize_legislation, summarize_meeting, summarize_micro, summarize_newsletter, summarize_paper, summarize_pull-requests, summarize_rpg_session, youtube_summary
+
+**VISUALIZE**: create_excalidraw_visualization, create_graph_from_input, create_idea_compass, create_investigation_visualization, create_keynote, create_logo, create_markmap_visualization, create_mermaid_visualization, create_mermaid_visualization_for_github, create_video_chapters, create_visualization, enrich_blog_post, t_visualize_mission_goals_projects
+
+**WISDOM**: extract_alpha, extract_article_wisdom, extract_book_ideas, extract_insights, extract_most_redeeming_thing, extract_recommendations, extract_wisdom, extract_wisdom_dm, extract_wisdom_nometa, extract_wisdom_short
+
+**WRITING**: analyze_prose_json, analyze_prose_pinker, apply_ul_tags, clean_text, compare_and_contrast, convert_to_markdown, create_5_sentence_summary, create_academic_paper, create_aphorisms, create_better_frame, create_design_document, create_diy, create_formal_email, create_hormozi_offer, create_keynote, create_micro_summary, create_newsletter_entry, create_prediction_block, create_prd, create_show_intro, create_story_explanation, create_summary, create_tags, create_user_story, enrich_blog_post, explain_docs, explain_terms, humanize, improve_academic_writing, improve_writing, label_and_rate, md_callout, official_pattern_template, recommend_talkpanel_topics, refine_design_document, summarize, summarize_debate, summarize_lecture, summarize_legislation, summarize_meeting, summarize_micro, summarize_newsletter, summarize_paper, summarize_rpg_session, t_create_opening_sentences, t_describe_life_outlook, t_extract_intro_sentences, t_extract_panel_topics, t_give_encouragement, t_year_in_review, transcribe_minutes, tweet, write_essay, write_essay_pg, write_hackerone_report, write_latex, write_micro_essay, write_pull-request
+
+## Workflow Suggestions
+
+- For complex analysis: First use an extract pattern, then an analyze pattern, finally a summarize pattern
+- For content creation: Use relevant create_patterns followed by improve_ patterns for refinement
+- For research projects: Combine extract_, analyze_, and summarize_ patterns in sequence
 
 # INPUT
-INPUT:
+
+INPUT:

data/patterns/suggest_pattern/user_updated.md

@@ -1,919 +0,0 @@
-# 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.

docs/CODE_OF_CONDUCT.md

@@ -0,0 +1,26 @@
+# Code of Conduct
+
+## Our Expectation
+
+We expect all contributors and community members to act with basic human decency and common sense.
+
+This project exists to help people augment their capabilities with AI, and we welcome contributions from anyone who shares this mission. We assume good faith and trust that everyone involved is here to build something valuable together.
+
+## Guidelines
+
+- **Be respectful**: Treat others as you'd want to be treated in a professional setting
+- **Be constructive**: Focus on the work and help make the project better
+- **Be collaborative**: We're all working toward the same goal - making Fabric more useful
+- **Use good judgment**: If you're not sure whether something is appropriate, it probably isn't
+
+## Reporting Issues
+
+If someone is being genuinely disruptive or harmful, please email the maintainers directly. We'll address legitimate concerns promptly and fairly.
+
+## Enforcement
+
+Maintainers reserve the right to remove content and restrict access for anyone who consistently acts in bad faith or disrupts the community.
+
+---
+
+*This project assumes contributors are adults who can work together professionally. If you can't do that, this isn't the right place for you.*

docs/CONTRIBUTING.md

@@ -0,0 +1,155 @@
+# Contributing to Fabric
+
+Thanks for contributing to Fabric! Here's what you need to know to get started quickly.
+
+## Quick Setup
+
+### Prerequisites
+
+- Go 1.24+ installed
+- Git configured with your details
+
+### Getting Started
+
+```bash
+# Clone and setup
+git clone https://github.com/danielmiessler/fabric.git
+cd fabric
+go build -o fabric ./cmd/fabric
+./fabric --setup
+
+# Run tests
+go test ./...
+```
+
+## Development Guidelines
+
+### Code Style
+
+- Follow standard Go conventions (`gofmt`, `golint`)
+- Use meaningful variable and function names
+- Write tests for new functionality
+- Keep functions focused and small
+
+### Commit Messages
+
+Use descriptive commit messages:
+
+```text
+feat: add new pattern for code analysis
+fix: resolve OAuth token refresh issue
+docs: update installation instructions
+```
+
+### Project Structure
+
+- `cmd/` - Executable commands
+- `internal/` - Private application code
+- `data/patterns/` - AI patterns
+- `docs/` - Documentation
+
+## Pull Request Process
+
+### Changelog Generation (REQUIRED)
+
+Before submitting your PR, generate a changelog entry:
+
+```bash
+cd cmd/generate_changelog
+go build -o generate_changelog .
+./generate_changelog --incoming-pr YOUR_PR_NUMBER
+```
+
+**Requirements:**
+
+- PR must be open and mergeable
+- Working directory must be clean
+- GitHub token available (GITHUB_TOKEN env var)
+
+**Optional flags:**
+
+- `--ai-summarize` - Enhanced AI-generated summaries
+- `--push` - Auto-push the changelog commit
+
+### PR Guidelines
+
+1. Fork the repository
+2. Create a feature branch
+3. Make your changes
+4. Write/update tests
+5. Generate changelog entry (see above)
+6. Submit PR with clear description
+
+### Review Process
+
+- PRs require maintainer review
+- Address feedback promptly
+- Keep PRs focused on single features/fixes
+- Update changelog if you make significant changes
+
+## Testing
+
+### Run Tests
+
+```bash
+# All tests
+go test ./...
+
+# Specific package
+go test ./internal/cli
+
+# With coverage
+go test -cover ./...
+```
+
+### Test Requirements
+
+- Unit tests for core functionality
+- Integration tests for external dependencies
+- Examples in documentation
+
+## Patterns
+
+### Creating Patterns
+
+Patterns go in `data/patterns/[pattern-name]/system.md`:
+
+```markdown
+# IDENTITY and PURPOSE
+You are an expert at...
+
+# STEPS
+- Step 1
+- Step 2
+
+# OUTPUT
+- Output format requirements
+
+# EXAMPLE
+Example output here
+```
+
+### Pattern Guidelines
+
+- Use clear, actionable language
+- Provide specific output formats
+- Include examples when helpful
+- Test with multiple AI providers
+
+## Documentation
+
+- Update README.md for new features
+- Add docs to `docs/` for complex features
+- Include usage examples
+- Keep documentation current
+
+## Getting Help
+
+- Check existing issues first
+- Ask questions in discussions
+- Tag maintainers for urgent issues
+- Be patient - maintainers are volunteers
+
+## License
+
+By contributing, you agree your contributions will be licensed under the MIT License.

docs/README.md

@@ -0,0 +1,88 @@
+# Fabric Documentation
+
+Welcome to the Fabric documentation! This directory contains detailed guides and technical documentation for various features and components of Fabric.
+
+## 📚 Available Documentation
+
+### Core Features
+
+**[Automated-Changelog-Usage.md](./Automated-Changelog-Usage.md)**
+Complete guide for developers on using the automated changelog system. Covers the workflow for generating PR changelog entries during development, including setup, validation, and CI/CD integration.
+
+**[YouTube-Processing.md](./YouTube-Processing.md)**
+Comprehensive guide for processing YouTube videos and playlists with Fabric. Covers transcript extraction, comment processing, metadata retrieval, and advanced yt-dlp configurations.
+
+**[Using-Speech-To-Text.md](./Using-Speech-To-Text.md)**
+Documentation for Fabric's speech-to-text capabilities using OpenAI's Whisper models. Learn how to transcribe audio and video files and process them through Fabric patterns.
+
+### User Interface & Experience
+
+**[Desktop-Notifications.md](./Desktop-Notifications.md)**
+Guide to setting up desktop notifications for Fabric commands. Useful for long-running tasks and multitasking scenarios with cross-platform notification support.
+
+**[Shell-Completions.md](./Shell-Completions.md)**
+Instructions for setting up intelligent tab completion for Fabric in Zsh, Bash, and Fish shells. Includes automated installation and manual setup options.
+
+**[Gemini-TTS.md](./Gemini-TTS.md)**
+Complete guide for using Google Gemini's text-to-speech features with Fabric. Covers voice selection, audio generation, and integration with Fabric patterns.
+
+### Development & Architecture
+
+**[Automated-ChangeLog.md](./Automated-ChangeLog.md)**
+Technical documentation outlining the automated CHANGELOG system architecture for CI/CD integration. Details the infrastructure and workflow for maintainers.
+
+**[Project-Restructured.md](./Project-Restructured.md)**
+Project restructuring plan and architectural decisions. Documents the transition to standard Go conventions and project organization improvements.
+
+**[NOTES.md](./NOTES.md)**
+Development notes on refactoring efforts, model management improvements, and architectural changes. Includes technical details on vendor and model abstraction.
+
+### Audio Resources
+
+**[voices/README.md](./voices/README.md)**
+Index of Gemini TTS voice samples demonstrating different AI voice characteristics available in Fabric.
+
+## 🗂️ Additional Resources
+
+### Configuration Files
+
+- `./notification-config.yaml` - Example notification configuration
+
+### Images
+
+- `images/` - Screenshots and visual documentation assets
+  - `fabric-logo-gif.gif` - Animated Fabric logo
+  - `fabric-summarize.png` - Screenshot of summarization feature
+  - `svelte-preview.png` - Web interface preview
+
+## 🚀 Quick Start
+
+New to Fabric? Start with these essential docs:
+
+1. **[../README.md](../README.md)** - Main project README with installation and basic usage
+2. **[Shell-Completions.md](./Shell-Completions.md)** - Set up tab completion for better CLI experience
+3. **[YouTube-Processing.md](./YouTube-Processing.md)** - Learn one of Fabric's most popular features
+4. **[Desktop-Notifications.md](./Desktop-Notifications.md)** - Get notified when long tasks complete
+
+## 🔧 For Contributors
+
+Contributing to Fabric? These docs are essential:
+
+1. **[./CONTRIBUTING.md](./CONTRIBUTING.md)** - Contribution guidelines and setup
+2. **[Automated-Changelog-Usage.md](./Automated-Changelog-Usage.md)** - Required workflow for PR submissions
+3. **[Project-Restructured.md](./Project-Restructured.md)** - Understanding project architecture
+4. **[NOTES.md](./NOTES.md)** - Current development priorities and patterns
+
+## 📝 Documentation Standards
+
+When adding new documentation:
+
+- Use clear, descriptive filenames
+- Include practical examples and use cases
+- Update this README index with your new docs
+- Follow the established markdown formatting conventions
+- Test all code examples before publication
+
+---
+
+*For general help and support, see [./SUPPORT.md](./SUPPORT.md)*

docs/SECURITY.md

@@ -0,0 +1,158 @@
+# Security Policy
+
+## Supported Versions
+
+We aim to provide security updates for the latest version of Fabric.
+
+We recommend always using the latest version of Fabric for security fixes and improvements.
+
+## Reporting Security Vulnerabilities
+
+**Please DO NOT report security vulnerabilities through public GitHub issues.**
+
+### Preferred Reporting Method
+
+Send security reports directly to: **<kayvan@sylvan.com>** and CC to the project maintainer at **<daniel@danielmiessler.com>**
+
+### What to Include
+
+Please provide the following information:
+
+1. **Vulnerability Type**: What kind of security issue (e.g., injection, authentication bypass, etc.)
+2. **Affected Components**: Which parts of Fabric are affected
+3. **Impact Assessment**: What could an attacker accomplish
+4. **Reproduction Steps**: Clear steps to reproduce the vulnerability
+5. **Proposed Fix**: If you have suggestions for remediation
+6. **Disclosure Timeline**: Your preferred timeline for public disclosure
+
+### Example Report Format
+
+```text
+Subject: [SECURITY] Brief description of vulnerability
+
+Vulnerability Type: SQL Injection
+Affected Component: Pattern database queries
+Impact: Potential data exposure
+Severity: High
+
+Reproduction Steps:
+1. Navigate to...
+2. Submit payload: ...
+3. Observe...
+
+Evidence:
+[Screenshots, logs, or proof of concept]
+
+Suggested Fix:
+Use parameterized queries instead of string concatenation...
+```
+
+## Security Considerations
+
+### API Keys and Secrets
+
+- Never commit API keys to the repository
+- Store secrets in environment variables or secure configuration
+- Use the built-in setup process for key management
+- Regularly rotate API keys
+
+### Input Validation
+
+- All user inputs are validated before processing
+- Special attention to pattern definitions and user content
+- URL validation for web scraping features
+
+### AI Provider Integration
+
+- Secure communication with AI providers (HTTPS/TLS)
+- Token handling follows provider best practices
+- No sensitive data logged or cached unencrypted
+
+### Network Security
+
+- Web server endpoints properly authenticated when required
+- CORS policies appropriately configured
+- Rate limiting implemented where necessary
+
+## Vulnerability Response Process
+
+1. **Report Received**: We'll acknowledge receipt within 24 hours
+2. **Initial Assessment**: We'll evaluate severity and impact within 72 hours
+3. **Investigation**: We'll investigate and develop fixes
+4. **Fix Development**: We'll create and test patches
+5. **Coordinated Disclosure**: We'll work with reporter on disclosure timeline
+6. **Release**: We'll release patched version with security advisory
+
+### Timeline Expectations
+
+- **Critical**: 1-7 days
+- **High**: 7-30 days
+- **Medium**: 30-90 days
+- **Low**: Next scheduled release
+
+## Bug Bounty
+
+We don't currently offer a formal bug bounty program, but we deeply appreciate security research and will:
+
+- Acknowledge contributors in release notes
+- Provide credit in security advisories
+- Consider swag or small rewards for significant findings
+
+## Security Best Practices for Users
+
+### Installation
+
+- Download Fabric only from official sources
+- Verify checksums when available
+- Keep installations up to date
+
+### Configuration
+
+- Use strong, unique API keys
+- Don't share configuration files containing secrets
+- Set appropriate file permissions on config directories
+
+### Usage
+
+- Be cautious with patterns that process sensitive data
+- Review AI provider terms for data handling
+- Consider using local models for sensitive content
+
+## Known Security Limitations
+
+### AI Provider Dependencies
+
+Fabric relies on external AI providers. Security depends partly on:
+
+- Provider security practices
+- Data transmission security
+- Provider data handling policies
+
+### Pattern Execution
+
+Custom patterns could potentially:
+
+- Process sensitive inputs inappropriately
+- Generate outputs containing sensitive information
+- Be used for adversarial prompt injection
+
+**Recommendation**: Review patterns carefully, especially those from untrusted sources.
+
+## Security Updates
+
+Security updates are distributed through:
+
+- GitHub Releases with security tags
+- Security advisories on GitHub
+- Project documentation updates
+
+Subscribe to the repository to receive notifications about security updates.
+
+## Contact
+
+For non-security issues, please use GitHub issues.
+For security concerns, email: **<kayvan@sylvan.com>** and CC to **<daniel@danielmiessler.com>**
+
+---
+
+*We take security seriously and appreciate the security research community's help in keeping Fabric secure.*

docs/SUPPORT.md

@@ -0,0 +1,148 @@
+# Support
+
+## Getting Help with Fabric
+
+Need help with Fabric? Here are the best ways to get assistance:
+
+## 📖 Documentation First
+
+Before reaching out, check these resources:
+
+- **[README.md](../README.md)** - Installation, usage, and examples
+- **[docs/](./README.md)** - Detailed documentation
+- **[Patterns](../data/patterns/)** - Browse available AI patterns
+
+## 🐛 Bug Reports
+
+Found a bug? Please create an issue:
+
+**[Report a Bug](https://github.com/danielmiessler/fabric/issues/new?template=bug.yml)**
+
+Include:
+
+- Fabric version (`fabric --version`)
+- Operating system
+- Steps to reproduce
+- Expected vs actual behavior
+- Error messages/logs
+
+## 💡 Feature Requests
+
+Have an idea for Fabric? We'd love to hear it:
+
+**[Request a Feature](https://github.com/danielmiessler/fabric/issues/new)**
+
+Describe:
+
+- What you want to achieve
+- Why it would be useful
+- How you envision it working
+- Any alternatives you've considered
+
+## 🤔 Questions & Discussions
+
+For general questions, usage help, or community discussion:
+
+**[GitHub Discussions](https://github.com/danielmiessler/fabric/discussions)**
+
+Great for:
+
+- "How do I...?" questions
+- Sharing patterns you've created
+- Getting community advice
+- Feature brainstorming
+
+## 🏷️ Issue Labels
+
+When creating issues, maintainers will add appropriate labels:
+
+- `bug` - Something isn't working
+- `enhancement` - New feature request
+- `documentation` - Documentation improvements
+- `help wanted` - Community contributions welcome
+- `good first issue` - Great for new contributors
+- `question` - General questions
+- `pattern` - Related to AI patterns
+
+## 📋 Issue Templates
+
+We provide templates to help you create detailed reports:
+
+- **Bug Report** - Structured bug reporting
+- **Feature Request** - Detailed feature proposals
+- **Pattern Submission** - New pattern contributions
+
+## 🔒 Security Issues
+
+**DO NOT create public issues for security vulnerabilities.**
+
+See our [Security Policy](./SECURITY.md) for proper reporting procedures.
+
+## ⚡ Response Times
+
+We're a community-driven project with volunteer maintainers:
+
+- **Bugs**: We aim to acknowledge within 48 hours
+- **Features**: Response time varies based on complexity
+- **Questions**: Community often responds quickly
+- **Security**: See security policy for timelines
+
+## 🛠️ Self-Help Tips
+
+Before creating an issue, try:
+
+1. **Update Fabric**: `go install github.com/danielmiessler/fabric/cmd/fabric@latest`
+2. **Check existing issues**: Someone might have the same problem
+3. **Run setup**: `fabric --setup` can fix configuration issues
+4. **Test minimal example**: Isolate the problem
+
+## 🤝 Community Guidelines
+
+When asking for help:
+
+- Be specific and provide context
+- Include relevant details and error messages
+- Be patient - maintainers are volunteers
+- Help others when you can
+- Say thanks when someone helps you
+
+## 📞 Emergency Contact
+
+For urgent security issues only:
+
+- Email: <security@fabric.ai> (if available)
+- Maintainer: <daniel@danielmiessler.com>
+
+## 🎯 What We Can Help With
+
+✅ **We can help with:**
+
+- Installation and setup issues
+- Usage questions and examples
+- Bug reports and fixes
+- Feature discussions
+- Pattern creation guidance
+- Integration questions
+
+❌ **We cannot help with:**
+
+- Custom development for your specific use case
+- Troubleshooting your specific AI provider issues
+- General AI or programming tutorials
+- Commercial support agreements
+
+## 💪 Contributing Back
+
+The best way to get help is to help others:
+
+- Answer questions in discussions
+- Improve documentation
+- Share useful patterns
+- Report bugs clearly
+- Review pull requests
+
+See our [Contributing Guide](./CONTRIBUTING.md) for details.
+
+---
+
+*Remember: We're all here to make Fabric better. Be kind, be helpful, and let's build something amazing together!*

docs/Shell-Completions.md

@@ -4,10 +4,24 @@ Fabric comes with shell completion support for Zsh, Bash, and Fish shells. These
 
 ## Quick Setup (Automated)
 
-For a quick automated installation, use the setup script:
+You can install completions without cloning the repo:
 
 ```bash
-# Run the automated setup script
+# No-clone install (Zsh/Bash/Fish supported)
+curl -fsSL https://raw.githubusercontent.com/danielmiessler/Fabric/refs/heads/main/completions/setup-completions.sh | sh
+
+# Optional: dry-run first
+curl -fsSL https://raw.githubusercontent.com/danielmiessler/Fabric/refs/heads/main/completions/setup-completions.sh | sh -s -- --dry-run
+
+# Optional: override the download source
+FABRIC_COMPLETIONS_BASE_URL="https://raw.githubusercontent.com/danielmiessler/Fabric/refs/heads/main/completions" \
+   sh -c "$(curl -fsSL https://raw.githubusercontent.com/danielmiessler/Fabric/refs/heads/main/completions/setup-completions.sh)"
+```
+
+Or, if you have the repository locally:
+
+```bash
+# Run the automated setup script from a cloned repo
 ./completions/setup-completions.sh
 
 # Or see what it would do first
@@ -22,6 +36,8 @@ The script will:
 - Install the completion file with the correct name
 - Provide instructions for enabling the completions
 
+If the completion files aren't present locally (e.g., when running via `curl`), the script will automatically download them from GitHub.
+
 For manual installation or troubleshooting, see the detailed instructions below.
 
 ## Manual Installation

docs/Using-Speech-To-Text.md

@@ -0,0 +1,139 @@
+# Using Speech-To-Text (STT) with Fabric
+
+Fabric supports speech-to-text transcription of audio and video files using OpenAI's transcription models. This feature allows you to convert spoken content into text that can then be processed through Fabric's patterns.
+
+## Overview
+
+The STT feature integrates OpenAI's Whisper and GPT-4o transcription models to convert audio/video files into text. The transcribed text is automatically passed as input to your chosen pattern or chat session.
+
+## Requirements
+
+- OpenAI API key configured in Fabric
+- For files larger than 25MB: `ffmpeg` installed on your system
+- Supported audio/video formats: `.mp3`, `.mp4`, `.mpeg`, `.mpga`, `.m4a`, `.wav`, `.webm`
+
+## Basic Usage
+
+### Simple Transcription
+
+To transcribe an audio file and send the result to a pattern:
+
+```bash
+fabric --transcribe-file /path/to/audio.mp3 --transcribe-model whisper-1 --pattern summarize
+```
+
+### Transcription Only
+
+To just transcribe a file without applying a pattern:
+
+```bash
+fabric --transcribe-file /path/to/audio.mp3 --transcribe-model whisper-1
+```
+
+## Command Line Flags
+
+### Required Flags
+
+- `--transcribe-file`: Path to the audio or video file to transcribe
+- `--transcribe-model`: Model to use for transcription (required when using transcription)
+
+### Optional Flags
+
+- `--split-media-file`: Automatically split files larger than 25MB into chunks using ffmpeg
+
+## Available Models
+
+You can list all available transcription models with:
+
+```bash
+fabric --list-transcription-models
+```
+
+Currently supported models:
+
+- `whisper-1`: OpenAI's Whisper model
+- `gpt-4o-mini-transcribe`: GPT-4o Mini transcription model
+- `gpt-4o-transcribe`: GPT-4o transcription model
+
+## File Size Handling
+
+### Files Under 25MB
+
+Files under the 25MB limit are processed directly without any special handling.
+
+### Files Over 25MB
+
+For files exceeding OpenAI's 25MB limit, you have two options:
+
+1. **Manual handling**: The command will fail with an error message suggesting to use `--split-media-file`
+2. **Automatic splitting**: Use the `--split-media-file` flag to automatically split the file into chunks
+
+```bash
+fabric --transcribe-file large_recording.mp4 --transcribe-model whisper-1 --split-media-file --pattern summarize
+```
+
+When splitting is enabled:
+
+- Fabric uses `ffmpeg` to split the file into 10-minute segments initially
+- If segments are still too large, it reduces the segment time by half repeatedly
+- All segments are transcribed and the results are concatenated
+- Temporary files are automatically cleaned up after processing
+
+## Integration with Patterns
+
+The transcribed text is seamlessly integrated into Fabric's workflow:
+
+1. File is transcribed using the specified model
+2. Transcribed text becomes the input message
+3. Text is sent to the specified pattern or chat session
+
+### Example Workflows
+
+**Meeting transcription and summarization:**
+
+```bash
+fabric --transcribe-file meeting.mp4 --transcribe-model gpt-4o-transcribe --pattern summarize
+```
+
+**Interview analysis:**
+
+```bash
+fabric --transcribe-file interview.mp3 --transcribe-model whisper-1 --pattern extract_insights
+```
+
+**Large video file processing:**
+
+```bash
+fabric --transcribe-file presentation.mp4 --transcribe-model gpt-4o-transcribe --split-media-file --pattern create_summary
+```
+
+## Error Handling
+
+Common error scenarios:
+
+- **Unsupported format**: Only the listed audio/video formats are supported
+- **File too large**: Use `--split-media-file` for files over 25MB
+- **Missing ffmpeg**: Install ffmpeg for automatic file splitting
+- **Invalid model**: Use `--list-transcription-models` to see available models
+- **Missing model**: The `--transcribe-model` flag is required when using `--transcribe-file`
+
+## Technical Details
+
+### Implementation
+
+- Transcription is handled in `internal/cli/transcribe.go:14`
+- OpenAI-specific implementation in `internal/plugins/ai/openai/openai_audio.go:41`
+- File splitting uses ffmpeg with configurable segment duration
+- Supports any vendor that implements the `transcriber` interface
+
+### Processing Pipeline
+
+1. CLI validates file format and size
+2. If file > 25MB and splitting enabled, file is split using ffmpeg
+3. Each file/segment is sent to OpenAI's transcription API
+4. Results are concatenated with spaces between segments
+5. Transcribed text is passed as input to the main Fabric pipeline
+
+### Vendor Support
+
+Currently, only OpenAI is supported for transcription, but the interface allows for future expansion to other vendors that provide transcription capabilities.

go.mod

@@ -5,7 +5,7 @@ go 1.24.0
 toolchain go1.24.2
 
 require (
-	github.com/anthropics/anthropic-sdk-go v1.7.0
+	github.com/anthropics/anthropic-sdk-go v1.9.1
 	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
@@ -21,7 +21,7 @@ require (
 	github.com/joho/godotenv v1.5.1
 	github.com/kballard/go-shellquote v0.0.0-20180428030007-95032a82bc51
 	github.com/mattn/go-sqlite3 v1.14.28
-	github.com/ollama/ollama v0.9.0
+	github.com/ollama/ollama v0.11.7
 	github.com/openai/openai-go v1.8.2
 	github.com/otiai10/copy v1.14.1
 	github.com/pkg/errors v0.9.1
@@ -117,7 +117,7 @@ require (
 	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/crypto v0.40.0 // indirect
 	golang.org/x/exp v0.0.0-20250531010427-b6e5de432a8b // indirect
 	golang.org/x/net v0.41.0 // indirect
 	golang.org/x/sync v0.16.0 // indirect

go.sum

@@ -17,8 +17,8 @@ github.com/andybalholm/cascadia v1.3.3 h1:AG2YHrzJIm4BZ19iwJ/DAua6Btl3IwJX+VI4kk
 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 v1.7.0 h1:5iVf5fG/2gqVsOce8mq02r/WdgqpokM/8DXg2Ue6C9Y=
-github.com/anthropics/anthropic-sdk-go v1.7.0/go.mod h1:3qSNQ5NrAmjC8A2ykuruSQttfqfdEYNZY5o8c0XSHB8=
+github.com/anthropics/anthropic-sdk-go v1.9.1 h1:raRhZKmayVSVZtLpLDd6IsMXvxLeeSU03/2IBTerWlg=
+github.com/anthropics/anthropic-sdk-go v1.9.1/go.mod h1:WTz31rIUHUHqai2UslPpw5CwXrQP3geYBioRV4WOLvE=
 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=
@@ -180,8 +180,8 @@ github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd h1:TRLaZ9cD/w
 github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd/go.mod h1:6dJC0mAP4ikYIbvyc7fijjWJddQyLn8Ig3JB5CqoB9Q=
 github.com/modern-go/reflect2 v1.0.2 h1:xBagoLtFs94CBntxluKeaWgTMpvLxC4ur3nMaC9Gz0M=
 github.com/modern-go/reflect2 v1.0.2/go.mod h1:yWuevngMOJpCy52FWWMvUC8ws7m/LJsjYzDa0/r8luk=
-github.com/ollama/ollama v0.9.0 h1:GvdGhi8G/QMnFrY0TMLDy1bXua+Ify8KTkFe4ZY/OZs=
-github.com/ollama/ollama v0.9.0/go.mod h1:aio9yQ7nc4uwIbn6S0LkGEPgn8/9bNQLL1nHuH+OcD0=
+github.com/ollama/ollama v0.11.7 h1:CuYjaJ/YEnvLDpJocJbbVdpdVFyGA/OP6lKFyzZD4dI=
+github.com/ollama/ollama v0.11.7/go.mod h1:9+1//yWPsDE2u+l1a5mpaKrYw4VdnSsRU3ioq5BvMms=
 github.com/onsi/gomega v1.34.1 h1:EUMJIKUjM8sKjYbtxQI9A4z2o+rruxnzNvpknOXie6k=
 github.com/onsi/gomega v1.34.1/go.mod h1:kU1QgUvBDLXBJq618Xvm2LUX6rSAfRaFRTcdOeDLwwY=
 github.com/openai/openai-go v1.8.2 h1:UqSkJ1vCOPUpz9Ka5tS0324EJFEuOvMc+lA/EarJWP8=
@@ -268,8 +268,8 @@ golang.org/x/crypto v0.13.0/go.mod h1:y6Z2r+Rw4iayiXXAIxJIDAJ1zMW4yaTpebo8fPOliY
 golang.org/x/crypto v0.19.0/go.mod h1:Iy9bg/ha4yyC70EfRS8jz+B6ybOBKMaSxLj6P6oBDfU=
 golang.org/x/crypto v0.23.0/go.mod h1:CKFgDieR+mRhux2Lsu27y0fO304Db0wZe70UKqHu0v8=
 golang.org/x/crypto v0.31.0/go.mod h1:kDsLvtWBEx7MV9tJOj9bnXsPbxwJQ6csT/x4KIN4Ssk=
-golang.org/x/crypto v0.39.0 h1:SHs+kF4LP+f+p14esP5jAoDpHU8Gu/v9lFRK6IT5imM=
-golang.org/x/crypto v0.39.0/go.mod h1:L+Xg3Wf6HoL4Bn4238Z6ft6KfEpN0tJGo53AAPC632U=
+golang.org/x/crypto v0.40.0 h1:r4x+VvoG5Fm+eJcxMaY8CQM7Lb0l1lsmjGBQ6s8BfKM=
+golang.org/x/crypto v0.40.0/go.mod h1:Qr1vMER5WyS2dfPHAlsOj01wgLbsyWtFn/aY+5+ZdxY=
 golang.org/x/exp v0.0.0-20250531010427-b6e5de432a8b h1:QoALfVG9rhQ/M7vYDScfPdWjGL9dlsVVM5VGh7aKoAA=
 golang.org/x/exp v0.0.0-20250531010427-b6e5de432a8b/go.mod h1:U6Lno4MTRCDY+Ba7aCcauB9T60gsv5s4ralQzP72ZoQ=
 golang.org/x/mod v0.6.0-dev.0.20220419223038-86c51ed26bb4/go.mod h1:jJ57K6gSWd91VN4djpZkiMVwK6gcyfeH4XE8wZrZaV4=
@@ -327,8 +327,8 @@ 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 v0.32.0 h1:DR4lr0TjUs3epypdhTOkMmuF5CDFJ/8pOnbzMZPQ7bg=
-golang.org/x/term v0.32.0/go.mod h1:uZG1FhGx848Sqfsq4/DlJr3xGGsYMu/L5GW4abiaEPQ=
+golang.org/x/term v0.33.0 h1:NuFncQrRcaRvVmgRkvM3j/F00gWIAlcmlB8ACEKmGIg=
+golang.org/x/term v0.33.0/go.mod h1:s18+ql9tYWp1IfpV9DmCtQDDSRBUjKaw9M1eAv5UeF0=
 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=

internal/cli/chat.go

@@ -9,6 +9,7 @@ import (
 
 	"github.com/danielmiessler/fabric/internal/core"
 	"github.com/danielmiessler/fabric/internal/domain"
+	debuglog "github.com/danielmiessler/fabric/internal/log"
 	"github.com/danielmiessler/fabric/internal/plugins/db/fsdb"
 	"github.com/danielmiessler/fabric/internal/tools/notifications"
 )
@@ -18,6 +19,19 @@ func handleChatProcessing(currentFlags *Flags, registry *core.PluginRegistry, me
 	if messageTools != "" {
 		currentFlags.AppendMessage(messageTools)
 	}
+	// Check for pattern-specific model via environment variable
+	if currentFlags.Pattern != "" && currentFlags.Model == "" {
+		envVar := "FABRIC_MODEL_" + strings.ToUpper(strings.ReplaceAll(currentFlags.Pattern, "-", "_"))
+		if modelSpec := os.Getenv(envVar); modelSpec != "" {
+			parts := strings.SplitN(modelSpec, "|", 2)
+			if len(parts) == 2 {
+				currentFlags.Vendor = parts[0]
+				currentFlags.Model = parts[1]
+			} else {
+				currentFlags.Model = modelSpec
+			}
+		}
+	}
 
 	var chatter *core.Chatter
 	if chatter, err = registry.GetChatter(currentFlags.Model, currentFlags.ModelContextLength,
@@ -122,7 +136,7 @@ func handleChatProcessing(currentFlags *Flags, registry *core.PluginRegistry, me
 	if chatOptions.Notification {
 		if err = sendNotification(chatOptions, chatReq.PatternName, result); err != nil {
 			// Log notification error but don't fail the main command
-			fmt.Fprintf(os.Stderr, "Failed to send notification: %v\n", err)
+			debuglog.Log("Failed to send notification: %v\n", err)
 		}
 	}
 

internal/cli/cli.go

@@ -3,10 +3,10 @@ package cli
 import (
 	"encoding/json"
 	"fmt"
-	"os"
 	"strings"
 
 	"github.com/danielmiessler/fabric/internal/core"
+	debuglog "github.com/danielmiessler/fabric/internal/log"
 	"github.com/danielmiessler/fabric/internal/plugins/ai/openai"
 	"github.com/danielmiessler/fabric/internal/tools/converter"
 	"github.com/danielmiessler/fabric/internal/tools/youtube"
@@ -34,7 +34,7 @@ func Cli(version string) (err error) {
 	var registry, err2 = initializeFabric()
 	if err2 != nil {
 		if !currentFlags.Setup {
-			fmt.Fprintln(os.Stderr, err2.Error())
+			debuglog.Log("%s\n", err2.Error())
 			currentFlags.Setup = true
 		}
 		// Return early if registry is nil to prevent panics in subsequent handlers
@@ -74,6 +74,15 @@ func Cli(version string) (err error) {
 		return
 	}
 
+	// Handle transcription if specified
+	if currentFlags.TranscribeFile != "" {
+		var transcriptionMessage string
+		if transcriptionMessage, err = handleTranscription(currentFlags, registry); err != nil {
+			return
+		}
+		currentFlags.Message = AppendMessage(currentFlags.Message, transcriptionMessage)
+	}
+
 	// Process HTML readability if needed
 	if currentFlags.HtmlReadability {
 		if msg, cleanErr := converter.HtmlReadability(currentFlags.Message); cleanErr != nil {

internal/cli/flags.go

@@ -13,6 +13,7 @@ import (
 
 	"github.com/danielmiessler/fabric/internal/chat"
 	"github.com/danielmiessler/fabric/internal/domain"
+	debuglog "github.com/danielmiessler/fabric/internal/log"
 	"github.com/danielmiessler/fabric/internal/util"
 	"github.com/jessevdk/go-flags"
 	"golang.org/x/text/language"
@@ -23,90 +24,90 @@ import (
 // Chat parameter defaults set in the struct tags must match domain.Default* constants
 
 type Flags struct {
-	Pattern                         string            `short:"p" long:"pattern" yaml:"pattern" description:"Choose a pattern from the available patterns" default:""`
-	PatternVariables                map[string]string `short:"v" long:"variable" description:"Values for pattern variables, e.g. -v=#role:expert -v=#points:30"`
-	Context                         string            `short:"C" long:"context" description:"Choose a context from the available contexts" default:""`
-	Session                         string            `long:"session" description:"Choose a session from the available sessions"`
-	Attachments                     []string          `short:"a" long:"attachment" description:"Attachment path or URL (e.g. for OpenAI image recognition messages)"`
-	Setup                           bool              `short:"S" long:"setup" description:"Run setup for all reconfigurable parts of fabric"`
-	Temperature                     float64           `short:"t" long:"temperature" yaml:"temperature" description:"Set temperature" default:"0.7"`
-	TopP                            float64           `short:"T" long:"topp" yaml:"topp" description:"Set top P" default:"0.9"`
-	Stream                          bool              `short:"s" long:"stream" yaml:"stream" description:"Stream"`
-	PresencePenalty                 float64           `short:"P" long:"presencepenalty" yaml:"presencepenalty" description:"Set presence penalty" default:"0.0"`
-	Raw                             bool              `short:"r" long:"raw" yaml:"raw" description:"Use the defaults of the model without sending chat options (like temperature etc.) and use the user role instead of the system role for patterns."`
-	FrequencyPenalty                float64           `short:"F" long:"frequencypenalty" yaml:"frequencypenalty" description:"Set frequency penalty" default:"0.0"`
-	ListPatterns                    bool              `short:"l" long:"listpatterns" description:"List all patterns"`
-	ListAllModels                   bool              `short:"L" long:"listmodels" description:"List all available models"`
-	ListAllContexts                 bool              `short:"x" long:"listcontexts" description:"List all contexts"`
-	ListAllSessions                 bool              `short:"X" long:"listsessions" description:"List all sessions"`
-	UpdatePatterns                  bool              `short:"U" long:"updatepatterns" description:"Update patterns"`
-	Message                         string            `hidden:"true" description:"Messages to send to chat"`
-	Copy                            bool              `short:"c" long:"copy" description:"Copy to clipboard"`
-	Model                           string            `short:"m" long:"model" yaml:"model" description:"Choose model"`
-	Vendor                          string            `short:"V" long:"vendor" yaml:"vendor" description:"Specify vendor for the selected model (e.g., -V \"LM Studio\" -m openai/gpt-oss-20b)"`
-	ModelContextLength              int               `long:"modelContextLength" yaml:"modelContextLength" description:"Model context length (only affects ollama)"`
-	Output                          string            `short:"o" long:"output" description:"Output to file" default:""`
-	OutputSession                   bool              `long:"output-session" description:"Output the entire session (also a temporary one) to the output file"`
-	LatestPatterns                  string            `short:"n" long:"latest" description:"Number of latest patterns to list" default:"0"`
-	ChangeDefaultModel              bool              `short:"d" long:"changeDefaultModel" description:"Change default model"`
-	YouTube                         string            `short:"y" long:"youtube" description:"YouTube video or play list \"URL\" to grab transcript, comments from it and send to chat or print it put to the console and store it in the output file"`
-	YouTubePlaylist                 bool              `long:"playlist" description:"Prefer playlist over video if both ids are present in the URL"`
-	YouTubeTranscript               bool              `long:"transcript" description:"Grab transcript from YouTube video and send to chat (it is used per default)."`
-	YouTubeTranscriptWithTimestamps bool              `long:"transcript-with-timestamps" description:"Grab transcript from YouTube video with timestamps and send to chat"`
-	YouTubeComments                 bool              `long:"comments" description:"Grab comments from YouTube video and send to chat"`
-	YouTubeMetadata                 bool              `long:"metadata" description:"Output video metadata"`
-	YtDlpArgs                       string            `long:"yt-dlp-args" yaml:"ytDlpArgs" description:"Additional arguments to pass to yt-dlp (e.g. '--cookies-from-browser brave')"`
-	Language                        string            `short:"g" long:"language" description:"Specify the Language Code for the chat, e.g. -g=en -g=zh" default:""`
-	ScrapeURL                       string            `short:"u" long:"scrape_url" description:"Scrape website URL to markdown using Jina AI"`
-	ScrapeQuestion                  string            `short:"q" long:"scrape_question" description:"Search question using Jina AI"`
-	Seed                            int               `short:"e" long:"seed" yaml:"seed" description:"Seed to be used for LMM generation"`
-	WipeContext                     string            `short:"w" long:"wipecontext" description:"Wipe context"`
-	WipeSession                     string            `short:"W" long:"wipesession" description:"Wipe session"`
-	PrintContext                    string            `long:"printcontext" description:"Print context"`
-	PrintSession                    string            `long:"printsession" description:"Print session"`
-	HtmlReadability                 bool              `long:"readability" description:"Convert HTML input into a clean, readable view"`
-	InputHasVars                    bool              `long:"input-has-vars" description:"Apply variables to user input"`
-	DryRun                          bool              `long:"dry-run" description:"Show what would be sent to the model without actually sending it"`
-	Serve                           bool              `long:"serve" description:"Serve the Fabric Rest API"`
-	ServeOllama                     bool              `long:"serveOllama" description:"Serve the Fabric Rest API with ollama endpoints"`
-	ServeAddress                    string            `long:"address" description:"The address to bind the REST API" default:":8080"`
-	ServeAPIKey                     string            `long:"api-key" description:"API key used to secure server routes" default:""`
-	Config                          string            `long:"config" description:"Path to YAML config file"`
-	Version                         bool              `long:"version" description:"Print current version"`
-	ListExtensions                  bool              `long:"listextensions" description:"List all registered extensions"`
-	AddExtension                    string            `long:"addextension" description:"Register a new extension from config file path"`
-	RemoveExtension                 string            `long:"rmextension" description:"Remove a registered extension by name"`
-	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)"`
-	Search                          bool              `long:"search" description:"Enable web search tool for supported models (Anthropic, OpenAI, Gemini)"`
-	SearchLocation                  string            `long:"search-location" description:"Set location for web search results (e.g., 'America/Los_Angeles')"`
-	ImageFile                       string            `long:"image-file" description:"Save generated image to specified file path (e.g., 'output.png')"`
-	ImageSize                       string            `long:"image-size" description:"Image dimensions: 1024x1024, 1536x1024, 1024x1536, auto (default: auto)"`
-	ImageQuality                    string            `long:"image-quality" description:"Image quality: low, medium, high, auto (default: auto)"`
-	ImageCompression                int               `long:"image-compression" description:"Compression level 0-100 for JPEG/WebP formats (default: not set)"`
-	ImageBackground                 string            `long:"image-background" description:"Background type: opaque, transparent (default: opaque, only for PNG/WebP)"`
-	SuppressThink                   bool              `long:"suppress-think" yaml:"suppressThink" description:"Suppress text enclosed in thinking tags"`
-	ThinkStartTag                   string            `long:"think-start-tag" yaml:"thinkStartTag" description:"Start tag for thinking sections" default:"<think>"`
-	ThinkEndTag                     string            `long:"think-end-tag" yaml:"thinkEndTag" description:"End tag for thinking sections" default:"</think>"`
-	DisableResponsesAPI             bool              `long:"disable-responses-api" yaml:"disableResponsesAPI" description:"Disable OpenAI Responses API (default: false)"`
-	Voice                           string            `long:"voice" yaml:"voice" description:"TTS voice name for supported models (e.g., Kore, Charon, Puck)" default:"Kore"`
-	ListGeminiVoices                bool              `long:"list-gemini-voices" description:"List all available Gemini TTS voices"`
-	Notification                    bool              `long:"notification" yaml:"notification" description:"Send desktop notification when command completes"`
-	NotificationCommand             string            `long:"notification-command" yaml:"notificationCommand" description:"Custom command to run for notifications (overrides built-in notifications)"`
-}
-
-var debug = false
-
-func Debugf(format string, a ...interface{}) {
-	if debug {
-		fmt.Printf("DEBUG: "+format, a...)
-	}
+	Pattern                         string               `short:"p" long:"pattern" yaml:"pattern" description:"Choose a pattern from the available patterns" default:""`
+	PatternVariables                map[string]string    `short:"v" long:"variable" description:"Values for pattern variables, e.g. -v=#role:expert -v=#points:30"`
+	Context                         string               `short:"C" long:"context" description:"Choose a context from the available contexts" default:""`
+	Session                         string               `long:"session" description:"Choose a session from the available sessions"`
+	Attachments                     []string             `short:"a" long:"attachment" description:"Attachment path or URL (e.g. for OpenAI image recognition messages)"`
+	Setup                           bool                 `short:"S" long:"setup" description:"Run setup for all reconfigurable parts of fabric"`
+	Temperature                     float64              `short:"t" long:"temperature" yaml:"temperature" description:"Set temperature" default:"0.7"`
+	TopP                            float64              `short:"T" long:"topp" yaml:"topp" description:"Set top P" default:"0.9"`
+	Stream                          bool                 `short:"s" long:"stream" yaml:"stream" description:"Stream"`
+	PresencePenalty                 float64              `short:"P" long:"presencepenalty" yaml:"presencepenalty" description:"Set presence penalty" default:"0.0"`
+	Raw                             bool                 `short:"r" long:"raw" yaml:"raw" description:"Use the defaults of the model without sending chat options (like temperature etc.) and use the user role instead of the system role for patterns."`
+	FrequencyPenalty                float64              `short:"F" long:"frequencypenalty" yaml:"frequencypenalty" description:"Set frequency penalty" default:"0.0"`
+	ListPatterns                    bool                 `short:"l" long:"listpatterns" description:"List all patterns"`
+	ListAllModels                   bool                 `short:"L" long:"listmodels" description:"List all available models"`
+	ListAllContexts                 bool                 `short:"x" long:"listcontexts" description:"List all contexts"`
+	ListAllSessions                 bool                 `short:"X" long:"listsessions" description:"List all sessions"`
+	UpdatePatterns                  bool                 `short:"U" long:"updatepatterns" description:"Update patterns"`
+	Message                         string               `hidden:"true" description:"Messages to send to chat"`
+	Copy                            bool                 `short:"c" long:"copy" description:"Copy to clipboard"`
+	Model                           string               `short:"m" long:"model" yaml:"model" description:"Choose model"`
+	Vendor                          string               `short:"V" long:"vendor" yaml:"vendor" description:"Specify vendor for the selected model (e.g., -V \"LM Studio\" -m openai/gpt-oss-20b)"`
+	ModelContextLength              int                  `long:"modelContextLength" yaml:"modelContextLength" description:"Model context length (only affects ollama)"`
+	Output                          string               `short:"o" long:"output" description:"Output to file" default:""`
+	OutputSession                   bool                 `long:"output-session" description:"Output the entire session (also a temporary one) to the output file"`
+	LatestPatterns                  string               `short:"n" long:"latest" description:"Number of latest patterns to list" default:"0"`
+	ChangeDefaultModel              bool                 `short:"d" long:"changeDefaultModel" description:"Change default model"`
+	YouTube                         string               `short:"y" long:"youtube" description:"YouTube video or play list \"URL\" to grab transcript, comments from it and send to chat or print it put to the console and store it in the output file"`
+	YouTubePlaylist                 bool                 `long:"playlist" description:"Prefer playlist over video if both ids are present in the URL"`
+	YouTubeTranscript               bool                 `long:"transcript" description:"Grab transcript from YouTube video and send to chat (it is used per default)."`
+	YouTubeTranscriptWithTimestamps bool                 `long:"transcript-with-timestamps" description:"Grab transcript from YouTube video with timestamps and send to chat"`
+	YouTubeComments                 bool                 `long:"comments" description:"Grab comments from YouTube video and send to chat"`
+	YouTubeMetadata                 bool                 `long:"metadata" description:"Output video metadata"`
+	YtDlpArgs                       string               `long:"yt-dlp-args" yaml:"ytDlpArgs" description:"Additional arguments to pass to yt-dlp (e.g. '--cookies-from-browser brave')"`
+	Language                        string               `short:"g" long:"language" description:"Specify the Language Code for the chat, e.g. -g=en -g=zh" default:""`
+	ScrapeURL                       string               `short:"u" long:"scrape_url" description:"Scrape website URL to markdown using Jina AI"`
+	ScrapeQuestion                  string               `short:"q" long:"scrape_question" description:"Search question using Jina AI"`
+	Seed                            int                  `short:"e" long:"seed" yaml:"seed" description:"Seed to be used for LMM generation"`
+	WipeContext                     string               `short:"w" long:"wipecontext" description:"Wipe context"`
+	WipeSession                     string               `short:"W" long:"wipesession" description:"Wipe session"`
+	PrintContext                    string               `long:"printcontext" description:"Print context"`
+	PrintSession                    string               `long:"printsession" description:"Print session"`
+	HtmlReadability                 bool                 `long:"readability" description:"Convert HTML input into a clean, readable view"`
+	InputHasVars                    bool                 `long:"input-has-vars" description:"Apply variables to user input"`
+	NoVariableReplacement           bool                 `long:"no-variable-replacement" description:"Disable pattern variable replacement"`
+	DryRun                          bool                 `long:"dry-run" description:"Show what would be sent to the model without actually sending it"`
+	Serve                           bool                 `long:"serve" description:"Serve the Fabric Rest API"`
+	ServeOllama                     bool                 `long:"serveOllama" description:"Serve the Fabric Rest API with ollama endpoints"`
+	ServeAddress                    string               `long:"address" description:"The address to bind the REST API" default:":8080"`
+	ServeAPIKey                     string               `long:"api-key" description:"API key used to secure server routes" default:""`
+	Config                          string               `long:"config" description:"Path to YAML config file"`
+	Version                         bool                 `long:"version" description:"Print current version"`
+	ListExtensions                  bool                 `long:"listextensions" description:"List all registered extensions"`
+	AddExtension                    string               `long:"addextension" description:"Register a new extension from config file path"`
+	RemoveExtension                 string               `long:"rmextension" description:"Remove a registered extension by name"`
+	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)"`
+	Search                          bool                 `long:"search" description:"Enable web search tool for supported models (Anthropic, OpenAI, Gemini)"`
+	SearchLocation                  string               `long:"search-location" description:"Set location for web search results (e.g., 'America/Los_Angeles')"`
+	ImageFile                       string               `long:"image-file" description:"Save generated image to specified file path (e.g., 'output.png')"`
+	ImageSize                       string               `long:"image-size" description:"Image dimensions: 1024x1024, 1536x1024, 1024x1536, auto (default: auto)"`
+	ImageQuality                    string               `long:"image-quality" description:"Image quality: low, medium, high, auto (default: auto)"`
+	ImageCompression                int                  `long:"image-compression" description:"Compression level 0-100 for JPEG/WebP formats (default: not set)"`
+	ImageBackground                 string               `long:"image-background" description:"Background type: opaque, transparent (default: opaque, only for PNG/WebP)"`
+	SuppressThink                   bool                 `long:"suppress-think" yaml:"suppressThink" description:"Suppress text enclosed in thinking tags"`
+	ThinkStartTag                   string               `long:"think-start-tag" yaml:"thinkStartTag" description:"Start tag for thinking sections" default:"<think>"`
+	ThinkEndTag                     string               `long:"think-end-tag" yaml:"thinkEndTag" description:"End tag for thinking sections" default:"</think>"`
+	DisableResponsesAPI             bool                 `long:"disable-responses-api" yaml:"disableResponsesAPI" description:"Disable OpenAI Responses API (default: false)"`
+	TranscribeFile                  string               `long:"transcribe-file" yaml:"transcribeFile" description:"Audio or video file to transcribe"`
+	TranscribeModel                 string               `long:"transcribe-model" yaml:"transcribeModel" description:"Model to use for transcription (separate from chat model)"`
+	SplitMediaFile                  bool                 `long:"split-media-file" yaml:"splitMediaFile" description:"Split audio/video files larger than 25MB using ffmpeg"`
+	Voice                           string               `long:"voice" yaml:"voice" description:"TTS voice name for supported models (e.g., Kore, Charon, Puck)" default:"Kore"`
+	ListGeminiVoices                bool                 `long:"list-gemini-voices" description:"List all available Gemini TTS voices"`
+	ListTranscriptionModels         bool                 `long:"list-transcription-models" description:"List all available transcription models"`
+	Notification                    bool                 `long:"notification" yaml:"notification" description:"Send desktop notification when command completes"`
+	NotificationCommand             string               `long:"notification-command" yaml:"notificationCommand" description:"Custom command to run for notifications (overrides built-in notifications)"`
+	Thinking                        domain.ThinkingLevel `long:"thinking" yaml:"thinking" description:"Set reasoning/thinking level (e.g., off, low, medium, high, or numeric tokens for Anthropic or Google Gemini)"`
+	Debug                           int                  `long:"debug" description:"Set debug level (0=off, 1=basic, 2=detailed, 3=trace)" default:"0"`
 }
 
 // Init Initialize flags. returns a Flags struct and an error
 func Init() (ret *Flags, err error) {
+	debuglog.SetLevel(debuglog.LevelFromInt(parseDebugLevel(os.Args[1:])))
 	// Track which yaml-configured flags were set on CLI
 	usedFlags := make(map[string]bool)
 	yamlArgsScan := os.Args[1:]
@@ -122,11 +123,11 @@ func Init() (ret *Flags, err error) {
 			shortTag := field.Tag.Get("short")
 			if longTag != "" {
 				flagToYamlTag[longTag] = yamlTag
-				Debugf("Mapped long flag %s to yaml tag %s\n", longTag, yamlTag)
+				debuglog.Debug(debuglog.Detailed, "Mapped long flag %s to yaml tag %s\n", longTag, yamlTag)
 			}
 			if shortTag != "" {
 				flagToYamlTag[shortTag] = yamlTag
-				Debugf("Mapped short flag %s to yaml tag %s\n", shortTag, yamlTag)
+				debuglog.Debug(debuglog.Detailed, "Mapped short flag %s to yaml tag %s\n", shortTag, yamlTag)
 			}
 		}
 	}
@@ -138,7 +139,7 @@ func Init() (ret *Flags, err error) {
 		if flag != "" {
 			if yamlTag, exists := flagToYamlTag[flag]; exists {
 				usedFlags[yamlTag] = true
-				Debugf("CLI flag used: %s (yaml: %s)\n", flag, yamlTag)
+				debuglog.Debug(debuglog.Detailed, "CLI flag used: %s (yaml: %s)\n", flag, yamlTag)
 			}
 		}
 	}
@@ -150,6 +151,7 @@ func Init() (ret *Flags, err error) {
 	if args, err = parser.Parse(); err != nil {
 		return
 	}
+	debuglog.SetLevel(debuglog.LevelFromInt(ret.Debug))
 
 	// Check to see if a ~/.config/fabric/config.yaml config file exists (only when user didn't specify a config)
 	if ret.Config == "" {
@@ -157,7 +159,7 @@ func Init() (ret *Flags, err error) {
 		if defaultConfigPath, err := util.GetDefaultConfigPath(); err == nil && defaultConfigPath != "" {
 			ret.Config = defaultConfigPath
 		} else if err != nil {
-			Debugf("Could not determine default config path: %v\n", err)
+			debuglog.Debug(debuglog.Detailed, "Could not determine default config path: %v\n", err)
 		}
 	}
 
@@ -182,13 +184,13 @@ func Init() (ret *Flags, err error) {
 					if flagField.CanSet() {
 						if yamlField.Type() != flagField.Type() {
 							if err := assignWithConversion(flagField, yamlField); err != nil {
-								Debugf("Type conversion failed for %s: %v\n", yamlTag, err)
+								debuglog.Debug(debuglog.Detailed, "Type conversion failed for %s: %v\n", yamlTag, err)
 								continue
 							}
 						} else {
 							flagField.Set(yamlField)
 						}
-						Debugf("Applied YAML value for %s: %v\n", yamlTag, yamlField.Interface())
+						debuglog.Debug(debuglog.Detailed, "Applied YAML value for %s: %v\n", yamlTag, yamlField.Interface())
 					}
 				}
 			}
@@ -214,6 +216,22 @@ func Init() (ret *Flags, err error) {
 	return
 }
 
+func parseDebugLevel(args []string) int {
+	for i := 0; i < len(args); i++ {
+		arg := args[i]
+		if arg == "--debug" && i+1 < len(args) {
+			if lvl, err := strconv.Atoi(args[i+1]); err == nil {
+				return lvl
+			}
+		} else if strings.HasPrefix(arg, "--debug=") {
+			if lvl, err := strconv.Atoi(strings.TrimPrefix(arg, "--debug=")); err == nil {
+				return lvl
+			}
+		}
+	}
+	return 0
+}
+
 func extractFlag(arg string) string {
 	var flag string
 	if strings.HasPrefix(arg, "--") {
@@ -283,7 +301,7 @@ func loadYAMLConfig(configPath string) (*Flags, error) {
 		return nil, fmt.Errorf("error parsing config file: %w", err)
 	}
 
-	Debugf("Config: %v\n", config)
+	debuglog.Debug(debuglog.Detailed, "Config: %v\n", config)
 
 	return config, nil
 }
@@ -438,6 +456,7 @@ func (o *Flags) BuildChatOptions() (ret *domain.ChatOptions, err error) {
 		FrequencyPenalty:    o.FrequencyPenalty,
 		Raw:                 o.Raw,
 		Seed:                o.Seed,
+		Thinking:            o.Thinking,
 		ModelContextLength:  o.ModelContextLength,
 		Search:              o.Search,
 		SearchLocation:      o.SearchLocation,
@@ -458,13 +477,14 @@ func (o *Flags) BuildChatOptions() (ret *domain.ChatOptions, err error) {
 
 func (o *Flags) BuildChatRequest(Meta string) (ret *domain.ChatRequest, err error) {
 	ret = &domain.ChatRequest{
-		ContextName:      o.Context,
-		SessionName:      o.Session,
-		PatternName:      o.Pattern,
-		StrategyName:     o.Strategy,
-		PatternVariables: o.PatternVariables,
-		InputHasVars:     o.InputHasVars,
-		Meta:             Meta,
+		ContextName:           o.Context,
+		SessionName:           o.Session,
+		PatternName:           o.Pattern,
+		StrategyName:          o.Strategy,
+		PatternVariables:      o.PatternVariables,
+		InputHasVars:          o.InputHasVars,
+		NoVariableReplacement: o.NoVariableReplacement,
+		Meta:                  Meta,
 	}
 
 	var message *chat.ChatCompletionMessage

internal/cli/flags_test.go

@@ -64,6 +64,7 @@ func TestBuildChatOptions(t *testing.T) {
 		FrequencyPenalty: 0.2,
 		Raw:              false,
 		Seed:             1,
+		Thinking:         domain.ThinkingLevel(""),
 		SuppressThink:    false,
 		ThinkStartTag:    "<think>",
 		ThinkEndTag:      "</think>",
@@ -88,6 +89,7 @@ func TestBuildChatOptionsDefaultSeed(t *testing.T) {
 		FrequencyPenalty: 0.2,
 		Raw:              false,
 		Seed:             0,
+		Thinking:         domain.ThinkingLevel(""),
 		SuppressThink:    false,
 		ThinkStartTag:    "<think>",
 		ThinkEndTag:      "</think>",

internal/cli/listing.go

@@ -5,6 +5,8 @@ import (
 	"os"
 	"strconv"
 
+	openai "github.com/openai/openai-go"
+
 	"github.com/danielmiessler/fabric/internal/core"
 	"github.com/danielmiessler/fabric/internal/plugins/ai"
 	"github.com/danielmiessler/fabric/internal/plugins/ai/gemini"
@@ -39,7 +41,7 @@ func handleListingCommands(currentFlags *Flags, fabricDb *fsdb.Db, registry *cor
 		if currentFlags.ShellCompleteOutput {
 			models.Print(true)
 		} else {
-			models.PrintWithVendor(false)
+			models.PrintWithVendor(false, registry.Defaults.Vendor.Value, registry.Defaults.Model.Value)
 		}
 		return true, nil
 	}
@@ -70,5 +72,30 @@ func handleListingCommands(currentFlags *Flags, fabricDb *fsdb.Db, registry *cor
 		return true, nil
 	}
 
+	if currentFlags.ListTranscriptionModels {
+		listTranscriptionModels(currentFlags.ShellCompleteOutput)
+		return true, nil
+	}
+
 	return false, nil
 }
+
+// listTranscriptionModels lists all available transcription models
+func listTranscriptionModels(shellComplete bool) {
+	models := []string{
+		string(openai.AudioModelWhisper1),
+		string(openai.AudioModelGPT4oMiniTranscribe),
+		string(openai.AudioModelGPT4oTranscribe),
+	}
+
+	if shellComplete {
+		for _, model := range models {
+			fmt.Println(model)
+		}
+	} else {
+		fmt.Println("Available transcription models:")
+		for _, model := range models {
+			fmt.Printf("  %s\n", model)
+		}
+	}
+}

internal/cli/output.go

@@ -7,6 +7,7 @@ import (
 	"strings"
 
 	"github.com/atotto/clipboard"
+	debuglog "github.com/danielmiessler/fabric/internal/log"
 )
 
 func CopyToClipboard(message string) (err error) {
@@ -30,7 +31,7 @@ func CreateOutputFile(message string, fileName string) (err error) {
 	if _, err = file.WriteString(message); err != nil {
 		err = fmt.Errorf("error writing to file: %v", err)
 	} else {
-		fmt.Fprintf(os.Stderr, "\n\n[Output also written to %s]\n", fileName)
+		debuglog.Log("\n\n[Output also written to %s]\n", fileName)
 	}
 	return
 }

internal/cli/transcribe.go

@@ -0,0 +1,35 @@
+package cli
+
+import (
+	"context"
+	"fmt"
+
+	"github.com/danielmiessler/fabric/internal/core"
+)
+
+type transcriber interface {
+	TranscribeFile(ctx context.Context, filePath, model string, split bool) (string, error)
+}
+
+func handleTranscription(flags *Flags, registry *core.PluginRegistry) (message string, err error) {
+	vendorName := flags.Vendor
+	if vendorName == "" {
+		vendorName = "OpenAI"
+	}
+	vendor, ok := registry.VendorManager.VendorsByName[vendorName]
+	if !ok {
+		return "", fmt.Errorf("vendor %s not configured", vendorName)
+	}
+	tr, ok := vendor.(transcriber)
+	if !ok {
+		return "", fmt.Errorf("vendor %s does not support audio transcription", vendorName)
+	}
+	model := flags.TranscribeModel
+	if model == "" {
+		return "", fmt.Errorf("transcription model is required (use --transcribe-model)")
+	}
+	if message, err = tr.TranscribeFile(context.Background(), flags.TranscribeFile, model, flags.SplitMediaFile); err != nil {
+		return
+	}
+	return
+}

internal/core/chatter.go

@@ -180,7 +180,7 @@ func (o *Chatter) BuildSession(request *domain.ChatRequest, raw bool) (session *
 	}
 
 	// Now we know request.Message is not nil, process template variables
-	if request.InputHasVars {
+	if request.InputHasVars && !request.NoVariableReplacement {
 		request.Message.Content, err = template.ApplyTemplate(request.Message.Content, request.PatternVariables, "")
 		if err != nil {
 			return nil, err
@@ -190,7 +190,12 @@ func (o *Chatter) BuildSession(request *domain.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)
+		var pattern *fsdb.Pattern
+		if request.NoVariableReplacement {
+			pattern, err = o.db.Patterns.GetWithoutVariables(request.PatternName, request.Message.Content)
+		} else {
+			pattern, err = o.db.Patterns.GetApplyVariables(request.PatternName, request.PatternVariables, request.Message.Content)
+		}
 
 		if err != nil {
 			return nil, fmt.Errorf("could not get pattern %s: %v", request.PatternName, err)

internal/core/plugin_registry.go

@@ -10,6 +10,7 @@ import (
 	"strconv"
 	"strings"
 
+	debuglog "github.com/danielmiessler/fabric/internal/log"
 	"github.com/danielmiessler/fabric/internal/plugins/ai/anthropic"
 	"github.com/danielmiessler/fabric/internal/plugins/ai/azure"
 	"github.com/danielmiessler/fabric/internal/plugins/ai/bedrock"
@@ -20,7 +21,7 @@ import (
 	"github.com/danielmiessler/fabric/internal/plugins/ai/ollama"
 	"github.com/danielmiessler/fabric/internal/plugins/ai/openai"
 	"github.com/danielmiessler/fabric/internal/plugins/ai/openai_compatible"
-	"github.com/danielmiessler/fabric/internal/plugins/ai/perplexity" // Added Perplexity plugin
+	"github.com/danielmiessler/fabric/internal/plugins/ai/perplexity"
 	"github.com/danielmiessler/fabric/internal/plugins/strategy"
 
 	"github.com/samber/lo"
@@ -339,7 +340,7 @@ func (o *PluginRegistry) GetChatter(model string, modelContextLength int, vendor
 		} else {
 			availableVendors := models.FindGroupsByItem(model)
 			if len(availableVendors) > 1 {
-				fmt.Fprintf(os.Stderr, "Warning: multiple vendors provide model %s: %s. Using %s. Specify --vendor to select a vendor.\n", model, strings.Join(availableVendors, ", "), availableVendors[0])
+				debuglog.Log("Warning: multiple vendors provide model %s: %s. Using %s. Specify --vendor to select a vendor.\n", model, strings.Join(availableVendors, ", "), availableVendors[0])
 			}
 			ret.vendor = vendorManager.FindByName(models.FindGroupsByItemFirst(model))
 		}

internal/core/plugin_registry_test.go

@@ -10,6 +10,7 @@ import (
 
 	"github.com/danielmiessler/fabric/internal/chat"
 	"github.com/danielmiessler/fabric/internal/domain"
+	debuglog "github.com/danielmiessler/fabric/internal/log"
 	"github.com/danielmiessler/fabric/internal/plugins"
 	"github.com/danielmiessler/fabric/internal/plugins/ai"
 	"github.com/danielmiessler/fabric/internal/plugins/db/fsdb"
@@ -72,7 +73,12 @@ func TestGetChatter_WarnsOnAmbiguousModel(t *testing.T) {
 	r, w, _ := os.Pipe()
 	oldStderr := os.Stderr
 	os.Stderr = w
-	defer func() { os.Stderr = oldStderr }()
+	// Redirect log output to our pipe to capture unconditional log messages
+	debuglog.SetOutput(w)
+	defer func() {
+		os.Stderr = oldStderr
+		debuglog.SetOutput(oldStderr)
+	}()
 
 	chatter, err := registry.GetChatter("shared-model", 0, "", "", false, false)
 	w.Close()
@@ -81,8 +87,10 @@ func TestGetChatter_WarnsOnAmbiguousModel(t *testing.T) {
 	if err != nil {
 		t.Fatalf("GetChatter() error = %v", err)
 	}
-	if chatter.vendor.GetName() != "VendorA" {
-		t.Fatalf("expected vendor VendorA, got %s", chatter.vendor.GetName())
+	// Verify that one of the valid vendors was selected (don't care which one due to map iteration randomness)
+	vendorName := chatter.vendor.GetName()
+	if vendorName != "VendorA" && vendorName != "VendorB" {
+		t.Fatalf("expected vendor VendorA or VendorB, got %s", vendorName)
 	}
 	if !strings.Contains(string(warning), "multiple vendors provide model shared-model") {
 		t.Fatalf("expected warning about multiple vendors, got %q", string(warning))

internal/domain/domain.go

@@ -13,15 +13,16 @@ const (
 )
 
 type ChatRequest struct {
-	ContextName      string
-	SessionName      string
-	PatternName      string
-	PatternVariables map[string]string
-	Message          *chat.ChatCompletionMessage
-	Language         string
-	Meta             string
-	InputHasVars     bool
-	StrategyName     string
+	ContextName           string
+	SessionName           string
+	PatternName           string
+	PatternVariables      map[string]string
+	Message               *chat.ChatCompletionMessage
+	Language              string
+	Meta                  string
+	InputHasVars          bool
+	NoVariableReplacement bool
+	StrategyName          string
 }
 
 type ChatOptions struct {
@@ -32,6 +33,7 @@ type ChatOptions struct {
 	FrequencyPenalty    float64
 	Raw                 bool
 	Seed                int
+	Thinking            ThinkingLevel
 	ModelContextLength  int
 	MaxTokens           int
 	Search              bool

internal/domain/thinking.go

@@ -0,0 +1,34 @@
+package domain
+
+// ThinkingLevel represents reasoning/thinking levels supported across providers.
+type ThinkingLevel string
+
+const (
+	ThinkingOff    ThinkingLevel = "off"
+	ThinkingLow    ThinkingLevel = "low"
+	ThinkingMedium ThinkingLevel = "medium"
+	ThinkingHigh   ThinkingLevel = "high"
+)
+
+// ThinkingBudgets defines standardized token budgets for reasoning-enabled models.
+// The map assigns a maximum token count to each ThinkingLevel, representing the
+// amount of context or computation that can be used for reasoning at that level.
+// These values (e.g., 1024 for low, 2048 for medium, 4096 for high) are used to
+// Token budget constants for each ThinkingLevel.
+// These values are chosen to align with typical context window sizes for LLMs at different reasoning levels.
+// Adjust these if model capabilities change.
+const (
+	// TokenBudgetLow is suitable for basic reasoning or smaller models (e.g., 1k context window).
+	TokenBudgetLow int64 = 1024
+	// TokenBudgetMedium is suitable for intermediate reasoning or mid-sized models (e.g., 2k context window).
+	TokenBudgetMedium int64 = 2048
+	// TokenBudgetHigh is suitable for advanced reasoning or large models (e.g., 4k context window).
+	TokenBudgetHigh int64 = 4096
+)
+
+// ThinkingBudgets defines standardized token budgets for reasoning-enabled models.
+var ThinkingBudgets = map[ThinkingLevel]int64{
+	ThinkingLow:    TokenBudgetLow,
+	ThinkingMedium: TokenBudgetMedium,
+	ThinkingHigh:   TokenBudgetHigh,
+}

internal/log/log.go

@@ -0,0 +1,78 @@
+package log
+
+import (
+	"fmt"
+	"io"
+	"os"
+	"sync"
+)
+
+// Level represents the debug verbosity.
+type Level int
+
+const (
+	// Off disables all debug output.
+	Off Level = iota
+	// Basic provides minimal debugging information.
+	Basic
+	// Detailed provides more verbose debugging.
+	Detailed
+	// Trace is the most verbose level.
+	Trace
+)
+
+var (
+	mu     sync.RWMutex
+	level  Level     = Off
+	output io.Writer = os.Stderr
+)
+
+// SetLevel sets the global debug level.
+func SetLevel(l Level) {
+	mu.Lock()
+	level = l
+	mu.Unlock()
+}
+
+// LevelFromInt converts an int to a Level.
+func LevelFromInt(i int) Level {
+	switch {
+	case i <= 0:
+		return Off
+	case i == 1:
+		return Basic
+	case i == 2:
+		return Detailed
+	case i >= 3:
+		return Trace
+	default:
+		return Off
+	}
+}
+
+// Debug writes a debug message if the global level permits.
+func Debug(l Level, format string, a ...interface{}) {
+	mu.RLock()
+	current := level
+	w := output
+	mu.RUnlock()
+	if current >= l {
+		fmt.Fprintf(w, "DEBUG: "+format, a...)
+	}
+}
+
+// Log writes a message unconditionally to stderr.
+// This is for important messages that should always be shown regardless of debug level.
+func Log(format string, a ...interface{}) {
+	mu.RLock()
+	w := output
+	mu.RUnlock()
+	fmt.Fprintf(w, format, a...)
+}
+
+// SetOutput allows overriding the output destination for debug logs.
+func SetOutput(w io.Writer) {
+	mu.Lock()
+	output = w
+	mu.Unlock()
+}

internal/plugins/ai/anthropic/anthropic.go

@@ -4,12 +4,14 @@ import (
 	"context"
 	"fmt"
 	"net/http"
+	"strconv"
 	"strings"
 
 	"github.com/anthropics/anthropic-sdk-go"
 	"github.com/anthropics/anthropic-sdk-go/option"
 	"github.com/danielmiessler/fabric/internal/chat"
 	"github.com/danielmiessler/fabric/internal/domain"
+	debuglog "github.com/danielmiessler/fabric/internal/log"
 	"github.com/danielmiessler/fabric/internal/plugins"
 	"github.com/danielmiessler/fabric/internal/util"
 )
@@ -49,6 +51,10 @@ func NewClient() (ret *Client) {
 		string(anthropic.ModelClaudeOpus4_1_20250805),
 	}
 
+	ret.modelBetas = map[string][]string{
+		string(anthropic.ModelClaudeSonnet4_20250514): {"context-1m-2025-08-07"},
+	}
+
 	return
 }
 
@@ -93,6 +99,7 @@ type Client struct {
 	maxTokens                  int
 	defaultRequiredUserMessage string
 	models                     []string
+	modelBetas                 map[string][]string
 
 	client anthropic.Client
 }
@@ -148,6 +155,26 @@ func (an *Client) ListModels() (ret []string, err error) {
 	return an.models, nil
 }
 
+func parseThinking(level domain.ThinkingLevel) (anthropic.ThinkingConfigParamUnion, bool) {
+	lower := strings.ToLower(string(level))
+	switch domain.ThinkingLevel(lower) {
+	case domain.ThinkingOff:
+		disabled := anthropic.NewThinkingConfigDisabledParam()
+		return anthropic.ThinkingConfigParamUnion{OfDisabled: &disabled}, true
+	case domain.ThinkingLow, domain.ThinkingMedium, domain.ThinkingHigh:
+		if budget, ok := domain.ThinkingBudgets[domain.ThinkingLevel(lower)]; ok {
+			return anthropic.ThinkingConfigParamOfEnabled(budget), true
+		}
+	default:
+		if tokens, err := strconv.ParseInt(lower, 10, 64); err == nil {
+			if tokens >= 1 && tokens <= 10000 {
+				return anthropic.ThinkingConfigParamOfEnabled(tokens), true
+			}
+		}
+	}
+	return anthropic.ThinkingConfigParamUnion{}, false
+}
+
 func (an *Client) SendStream(
 	msgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions, channel chan string,
 ) (err error) {
@@ -160,7 +187,17 @@ func (an *Client) SendStream(
 
 	ctx := context.Background()
 
-	stream := an.client.Messages.NewStreaming(ctx, an.buildMessageParams(messages, opts))
+	params := an.buildMessageParams(messages, opts)
+	betas := an.modelBetas[opts.Model]
+	var reqOpts []option.RequestOption
+	if len(betas) > 0 {
+		reqOpts = append(reqOpts, option.WithHeader("anthropic-beta", strings.Join(betas, ",")))
+	}
+	stream := an.client.Messages.NewStreaming(ctx, params, reqOpts...)
+	if stream.Err() != nil && len(betas) > 0 {
+		debuglog.Debug(debuglog.Basic, "Anthropic beta feature %s failed: %v\n", strings.Join(betas, ","), stream.Err())
+		stream = an.client.Messages.NewStreaming(ctx, params)
+	}
 
 	for stream.Next() {
 		event := stream.Current()
@@ -226,6 +263,11 @@ func (an *Client) buildMessageParams(msgs []anthropic.MessageParam, opts *domain
 			{OfWebSearchTool20250305: &webTool},
 		}
 	}
+
+	if t, ok := parseThinking(opts.Thinking); ok {
+		params.Thinking = t
+	}
+
 	return
 }
 
@@ -239,8 +281,21 @@ func (an *Client) Send(ctx context.Context, msgs []*chat.ChatCompletionMessage,
 	}
 
 	var message *anthropic.Message
-	if message, err = an.client.Messages.New(ctx, an.buildMessageParams(messages, opts)); err != nil {
-		return
+	params := an.buildMessageParams(messages, opts)
+	betas := an.modelBetas[opts.Model]
+	var reqOpts []option.RequestOption
+	if len(betas) > 0 {
+		reqOpts = append(reqOpts, option.WithHeader("anthropic-beta", strings.Join(betas, ",")))
+	}
+	if message, err = an.client.Messages.New(ctx, params, reqOpts...); err != nil {
+		if len(betas) > 0 {
+			debuglog.Debug(debuglog.Basic, "Anthropic beta feature %s failed: %v\n", strings.Join(betas, ","), err)
+			if message, err = an.client.Messages.New(ctx, params); err != nil {
+				return
+			}
+		} else {
+			return
+		}
 	}
 
 	var textParts []string

internal/plugins/ai/anthropic/anthropic_test.go

@@ -168,6 +168,15 @@ func TestBuildMessageParams_WithSearchAndLocation(t *testing.T) {
 	}
 }
 
+func TestModelBetasConfiguration(t *testing.T) {
+	client := NewClient()
+	model := string(anthropic.ModelClaudeSonnet4_20250514)
+	betas, ok := client.modelBetas[model]
+	if !ok || len(betas) != 1 || betas[0] != "context-1m-2025-08-07" {
+		t.Errorf("expected beta mapping for %s", model)
+	}
+}
+
 func TestCitationFormatting(t *testing.T) {
 	// Test the citation formatting logic by creating a mock message with citations
 	message := &anthropic.Message{

internal/plugins/ai/anthropic/oauth.go

@@ -9,11 +9,11 @@ import (
 	"fmt"
 	"io"
 	"net/http"
-	"os"
 	"os/exec"
 	"strings"
 	"time"
 
+	debuglog "github.com/danielmiessler/fabric/internal/log"
 	"github.com/danielmiessler/fabric/internal/util"
 	"golang.org/x/oauth2"
 )
@@ -46,8 +46,13 @@ func (t *OAuthTransport) RoundTrip(req *http.Request) (*http.Response, error) {
 	// Add OAuth Bearer token
 	newReq.Header.Set("Authorization", "Bearer "+token)
 
-	// Add the anthropic-beta header for OAuth
-	newReq.Header.Set("anthropic-beta", "oauth-2025-04-20")
+	// Add the anthropic-beta header for OAuth, preserving existing betas
+	existing := newReq.Header.Get("anthropic-beta")
+	beta := "oauth-2025-04-20"
+	if existing != "" {
+		beta = existing + "," + beta
+	}
+	newReq.Header.Set("anthropic-beta", beta)
 
 	// Set User-Agent to match AI SDK exactly
 	newReq.Header.Set("User-Agent", "ai-sdk/anthropic")
@@ -72,7 +77,7 @@ func (t *OAuthTransport) getValidToken(tokenIdentifier string) (string, error) {
 	}
 	// If no token exists, run OAuth flow
 	if token == nil {
-		fmt.Fprintln(os.Stderr, "No OAuth token found, initiating authentication...")
+		debuglog.Log("No OAuth token found, initiating authentication...\n")
 		newAccessToken, err := RunOAuthFlow(tokenIdentifier)
 		if err != nil {
 			return "", fmt.Errorf("failed to authenticate: %w", err)
@@ -82,11 +87,11 @@ func (t *OAuthTransport) getValidToken(tokenIdentifier string) (string, error) {
 
 	// Check if token needs refresh (5 minute buffer)
 	if token.IsExpired(5) {
-		fmt.Fprintln(os.Stderr, "OAuth token expired, refreshing...")
+		debuglog.Log("OAuth token expired, refreshing...\n")
 		newAccessToken, err := RefreshToken(tokenIdentifier)
 		if err != nil {
 			// If refresh fails, try re-authentication
-			fmt.Fprintln(os.Stderr, "Token refresh failed, re-authenticating...")
+			debuglog.Log("Token refresh failed, re-authenticating...\n")
 			newAccessToken, err = RunOAuthFlow(tokenIdentifier)
 			if err != nil {
 				return "", fmt.Errorf("failed to refresh or re-authenticate: %w", err)
@@ -138,13 +143,13 @@ func RunOAuthFlow(tokenIdentifier string) (token string, err error) {
 		if err == nil && existingToken != nil {
 			// If token exists but is expired, try refreshing first
 			if existingToken.IsExpired(5) {
-				fmt.Fprintln(os.Stderr, "Found expired OAuth token, attempting refresh...")
+				debuglog.Log("Found expired OAuth token, attempting refresh...\n")
 				refreshedToken, refreshErr := RefreshToken(tokenIdentifier)
 				if refreshErr == nil {
-					fmt.Fprintln(os.Stderr, "Token refresh successful")
+					debuglog.Log("Token refresh successful\n")
 					return refreshedToken, nil
 				}
-				fmt.Fprintf(os.Stderr, "Token refresh failed (%v), proceeding with full OAuth flow...\n", refreshErr)
+				debuglog.Log("Token refresh failed (%v), proceeding with full OAuth flow...\n", refreshErr)
 			} else {
 				// Token exists and is still valid
 				return existingToken.AccessToken, nil
@@ -171,10 +176,10 @@ func RunOAuthFlow(tokenIdentifier string) (token string, err error) {
 		oauth2.SetAuthURLParam("state", verifier),
 	)
 
-	fmt.Fprintln(os.Stderr, "Open the following URL in your browser. Fabric would like to authorize:")
-	fmt.Fprintln(os.Stderr, authURL)
+	debuglog.Log("Open the following URL in your browser. Fabric would like to authorize:\n")
+	debuglog.Log("%s\n", authURL)
 	openBrowser(authURL)
-	fmt.Fprint(os.Stderr, "Paste the authorization code here: ")
+	debuglog.Log("Paste the authorization code here: ")
 	var code string
 	fmt.Scanln(&code)
 	parts := strings.SplitN(code, "#", 2)

internal/plugins/ai/dryrun/dryrun.go

@@ -87,6 +87,9 @@ func (c *Client) formatOptions(opts *domain.ChatOptions) string {
 	if opts.ImageFile != "" {
 		builder.WriteString(fmt.Sprintf("ImageFile: %s\n", opts.ImageFile))
 	}
+	if opts.Thinking != "" {
+		builder.WriteString(fmt.Sprintf("Thinking: %s\n", string(opts.Thinking)))
+	}
 	if opts.SuppressThink {
 		builder.WriteString("SuppressThink: enabled\n")
 		builder.WriteString(fmt.Sprintf("Thinking Start Tag: %s\n", opts.ThinkStartTag))

internal/plugins/ai/gemini/gemini.go

@@ -6,6 +6,7 @@ import (
 	"encoding/binary"
 	"fmt"
 	"regexp"
+	"strconv"
 	"strings"
 
 	"github.com/danielmiessler/fabric/internal/chat"
@@ -170,6 +171,25 @@ func (o *Client) NeedsRawMode(modelName string) bool {
 	return false
 }
 
+func parseThinkingConfig(level domain.ThinkingLevel) (*genai.ThinkingConfig, bool) {
+	lower := strings.ToLower(strings.TrimSpace(string(level)))
+	switch domain.ThinkingLevel(lower) {
+	case "", domain.ThinkingOff:
+		return nil, false
+	case domain.ThinkingLow, domain.ThinkingMedium, domain.ThinkingHigh:
+		if budget, ok := domain.ThinkingBudgets[domain.ThinkingLevel(lower)]; ok {
+			b := int32(budget)
+			return &genai.ThinkingConfig{IncludeThoughts: true, ThinkingBudget: &b}, true
+		}
+	default:
+		if tokens, err := strconv.ParseInt(lower, 10, 32); err == nil && tokens > 0 {
+			t := int32(tokens)
+			return &genai.ThinkingConfig{IncludeThoughts: true, ThinkingBudget: &t}, true
+		}
+	}
+	return nil, false
+}
+
 // buildGenerateContentConfig constructs the generation config with optional tools.
 // When search is enabled it injects the Google Search tool. The optional search
 // location accepts either:
@@ -201,6 +221,10 @@ func (o *Client) buildGenerateContentConfig(opts *domain.ChatOptions) (*genai.Ge
 		}
 	}
 
+	if tc, ok := parseThinkingConfig(opts.Thinking); ok {
+		cfg.ThinkingConfig = tc
+	}
+
 	return cfg, nil
 }
 

internal/plugins/ai/gemini/gemini_test.go

@@ -129,6 +129,38 @@ func TestBuildGenerateContentConfig_LanguageCodeNormalization(t *testing.T) {
 	}
 }
 
+func TestBuildGenerateContentConfig_Thinking(t *testing.T) {
+	client := &Client{}
+	opts := &domain.ChatOptions{Thinking: domain.ThinkingLow}
+
+	cfg, err := client.buildGenerateContentConfig(opts)
+	if err != nil {
+		t.Fatalf("unexpected error: %v", err)
+	}
+	if cfg.ThinkingConfig == nil || !cfg.ThinkingConfig.IncludeThoughts {
+		t.Fatalf("expected thinking config with thoughts included")
+	}
+	if cfg.ThinkingConfig.ThinkingBudget == nil || *cfg.ThinkingConfig.ThinkingBudget != int32(domain.TokenBudgetLow) {
+		t.Errorf("expected thinking budget %d, got %+v", domain.TokenBudgetLow, cfg.ThinkingConfig.ThinkingBudget)
+	}
+}
+
+func TestBuildGenerateContentConfig_ThinkingTokens(t *testing.T) {
+	client := &Client{}
+	opts := &domain.ChatOptions{Thinking: domain.ThinkingLevel("123")}
+
+	cfg, err := client.buildGenerateContentConfig(opts)
+	if err != nil {
+		t.Fatalf("unexpected error: %v", err)
+	}
+	if cfg.ThinkingConfig == nil || cfg.ThinkingConfig.ThinkingBudget == nil {
+		t.Fatalf("expected thinking config with budget")
+	}
+	if *cfg.ThinkingConfig.ThinkingBudget != 123 {
+		t.Errorf("expected thinking budget 123, got %d", *cfg.ThinkingConfig.ThinkingBudget)
+	}
+}
+
 func TestCitationFormatting(t *testing.T) {
 	client := &Client{}
 	response := &genai.GenerateContentResponse{

internal/plugins/ai/models.go

@@ -18,7 +18,8 @@ type VendorsModels struct {
 
 // PrintWithVendor prints models including their vendor on each line.
 // When shellCompleteList is true, output is suitable for shell completion.
-func (o *VendorsModels) PrintWithVendor(shellCompleteList bool) {
+// Default vendor and model are highlighted with an asterisk.
+func (o *VendorsModels) PrintWithVendor(shellCompleteList bool, defaultVendor, defaultModel string) {
 	if !shellCompleteList {
 		fmt.Printf("\n%v:\n", o.SelectionLabel)
 	}
@@ -42,7 +43,11 @@ func (o *VendorsModels) PrintWithVendor(shellCompleteList bool) {
 			if shellCompleteList {
 				fmt.Printf("%s|%s\n", groupItems.Group, item)
 			} else {
-				fmt.Printf("\t[%d]\t%s|%s\n", currentItemIndex, groupItems.Group, item)
+				mark := "       "
+				if strings.EqualFold(groupItems.Group, defaultVendor) && strings.EqualFold(item, defaultModel) {
+					mark = "      *"
+				}
+				fmt.Printf("%s\t[%d]\t%s|%s\n", mark, currentItemIndex, groupItems.Group, item)
 			}
 		}
 	}

internal/plugins/ai/models_test.go

@@ -1,6 +1,9 @@
 package ai
 
 import (
+	"io"
+	"os"
+	"strings"
 	"testing"
 )
 
@@ -31,3 +34,23 @@ func TestFindVendorsByModel(t *testing.T) {
 		t.Fatalf("FindVendorsByModel() = %v, want %v", foundVendors, []string{"vendor1"})
 	}
 }
+
+func TestPrintWithVendorMarksDefault(t *testing.T) {
+	vendors := NewVendorsModels()
+	vendors.AddGroupItems("vendor1", []string{"model1"}...)
+	vendors.AddGroupItems("vendor2", []string{"model2"}...)
+
+	r, w, _ := os.Pipe()
+	oldStdout := os.Stdout
+	os.Stdout = w
+
+	vendors.PrintWithVendor(false, "vendor2", "model2")
+
+	w.Close()
+	os.Stdout = oldStdout
+	out, _ := io.ReadAll(r)
+
+	if !strings.Contains(string(out), "      *\t[2]\tvendor2|model2") {
+		t.Fatalf("default model not marked: %s", out)
+	}
+}

internal/plugins/ai/openai/chat_completions.go

@@ -85,6 +85,9 @@ func (o *Client) buildChatCompletionParams(
 			ret.Seed = openai.Int(int64(opts.Seed))
 		}
 	}
+	if eff, ok := parseReasoningEffort(opts.Thinking); ok {
+		ret.ReasoningEffort = eff
+	}
 	return
 }
 

internal/plugins/ai/openai/openai.go

@@ -184,6 +184,19 @@ func (o *Client) NeedsRawMode(modelName string) bool {
 	return slices.Contains(openAIModelsNeedingRaw, modelName)
 }
 
+func parseReasoningEffort(level domain.ThinkingLevel) (shared.ReasoningEffort, bool) {
+	switch domain.ThinkingLevel(strings.ToLower(string(level))) {
+	case domain.ThinkingLow:
+		return shared.ReasoningEffortLow, true
+	case domain.ThinkingMedium:
+		return shared.ReasoningEffortMedium, true
+	case domain.ThinkingHigh:
+		return shared.ReasoningEffortHigh, true
+	default:
+		return "", false
+	}
+}
+
 func (o *Client) buildResponseParams(
 	inputMsgs []*chat.ChatCompletionMessage, opts *domain.ChatOptions,
 ) (ret responses.ResponseNewParams) {
@@ -229,6 +242,10 @@ func (o *Client) buildResponseParams(
 		ret.Tools = tools
 	}
 
+	if eff, ok := parseReasoningEffort(opts.Thinking); ok {
+		ret.Reasoning = shared.ReasoningParam{Effort: eff}
+	}
+
 	if !opts.Raw {
 		ret.Temperature = openai.Float(opts.Temperature)
 		if opts.TopP != 0 {

internal/plugins/ai/openai/openai_audio.go

@@ -0,0 +1,153 @@
+package openai
+
+import (
+	"bytes"
+	"context"
+	"fmt"
+	"os"
+	"os/exec"
+	"path/filepath"
+	"slices"
+	"sort"
+	"strings"
+
+	debuglog "github.com/danielmiessler/fabric/internal/log"
+
+	openai "github.com/openai/openai-go"
+)
+
+// MaxAudioFileSize defines the maximum allowed size for audio uploads (25MB).
+const MaxAudioFileSize int64 = 25 * 1024 * 1024
+
+// AllowedTranscriptionModels lists the models supported for transcription.
+var AllowedTranscriptionModels = []string{
+	string(openai.AudioModelWhisper1),
+	string(openai.AudioModelGPT4oMiniTranscribe),
+	string(openai.AudioModelGPT4oTranscribe),
+}
+
+// allowedAudioExtensions defines the supported input file extensions.
+var allowedAudioExtensions = map[string]struct{}{
+	".mp3":  {},
+	".mp4":  {},
+	".mpeg": {},
+	".mpga": {},
+	".m4a":  {},
+	".wav":  {},
+	".webm": {},
+}
+
+// TranscribeFile transcribes the given audio file using the specified model. If the file
+// exceeds the size limit, it can optionally be split into chunks using ffmpeg.
+func (o *Client) TranscribeFile(ctx context.Context, filePath, model string, split bool) (string, error) {
+	if ctx == nil {
+		ctx = context.Background()
+	}
+
+	if !slices.Contains(AllowedTranscriptionModels, model) {
+		return "", fmt.Errorf("model '%s' is not supported for transcription", model)
+	}
+
+	ext := strings.ToLower(filepath.Ext(filePath))
+	if _, ok := allowedAudioExtensions[ext]; !ok {
+		return "", fmt.Errorf("unsupported audio format '%s'", ext)
+	}
+
+	info, err := os.Stat(filePath)
+	if err != nil {
+		return "", err
+	}
+
+	var files []string
+	var cleanup func()
+	if info.Size() > MaxAudioFileSize {
+		if !split {
+			return "", fmt.Errorf("file %s exceeds 25MB limit; use --split-media-file to enable automatic splitting", filePath)
+		}
+		debuglog.Log("File %s is larger than the size limit... breaking it up into chunks...\n", filePath)
+		if files, cleanup, err = splitAudioFile(filePath, ext, MaxAudioFileSize); err != nil {
+			return "", err
+		}
+		defer cleanup()
+	} else {
+		files = []string{filePath}
+	}
+
+	var builder strings.Builder
+	for i, f := range files {
+		debuglog.Log("Using model %s to transcribe part %d (file name: %s)...\n", model, i+1, f)
+		var chunk *os.File
+		if chunk, err = os.Open(f); err != nil {
+			return "", err
+		}
+		params := openai.AudioTranscriptionNewParams{
+			File:  chunk,
+			Model: openai.AudioModel(model),
+		}
+		var resp *openai.Transcription
+		resp, err = o.ApiClient.Audio.Transcriptions.New(ctx, params)
+		chunk.Close()
+		if err != nil {
+			return "", err
+		}
+		if i > 0 {
+			builder.WriteString(" ")
+		}
+		builder.WriteString(resp.Text)
+	}
+
+	return builder.String(), nil
+}
+
+// splitAudioFile splits the source file into chunks smaller than maxSize using ffmpeg.
+// It returns the list of chunk file paths and a cleanup function.
+func splitAudioFile(src, ext string, maxSize int64) (files []string, cleanup func(), err error) {
+	if _, err = exec.LookPath("ffmpeg"); err != nil {
+		return nil, nil, fmt.Errorf("ffmpeg not found: please install it")
+	}
+
+	var dir string
+	if dir, err = os.MkdirTemp("", "fabric-audio-*"); err != nil {
+		return nil, nil, err
+	}
+	cleanup = func() { os.RemoveAll(dir) }
+
+	segmentTime := 600 // start with 10 minutes
+	for {
+		pattern := filepath.Join(dir, "chunk-%03d"+ext)
+		debuglog.Log("Running ffmpeg to split audio into %d-second chunks...\n", segmentTime)
+		cmd := exec.Command("ffmpeg", "-y", "-i", src, "-f", "segment", "-segment_time", fmt.Sprintf("%d", segmentTime), "-c", "copy", pattern)
+		var stderr bytes.Buffer
+		cmd.Stderr = &stderr
+		if err = cmd.Run(); err != nil {
+			return nil, cleanup, fmt.Errorf("ffmpeg failed: %v: %s", err, stderr.String())
+		}
+
+		if files, err = filepath.Glob(filepath.Join(dir, "chunk-*"+ext)); err != nil {
+			return nil, cleanup, err
+		}
+		sort.Strings(files)
+
+		tooBig := false
+		for _, f := range files {
+			var info os.FileInfo
+			if info, err = os.Stat(f); err != nil {
+				return nil, cleanup, err
+			}
+			if info.Size() > maxSize {
+				tooBig = true
+				break
+			}
+		}
+		if !tooBig {
+			return files, cleanup, nil
+		}
+		for _, f := range files {
+			_ = os.Remove(f)
+		}
+		if segmentTime <= 1 {
+			return nil, cleanup, fmt.Errorf("unable to split file into acceptable size chunks")
+		}
+		segmentTime /= 2
+	}
+}

internal/plugins/ai/openai_compatible/providers_config.go

@@ -102,6 +102,11 @@ var ProviderMap = map[string]ProviderConfig{
 		BaseURL:             "https://api.together.xyz/v1",
 		ImplementsResponses: false,
 	},
+	"Venice AI": {
+		Name:                "Venice AI",
+		BaseURL:             "https://api.venice.ai/api/v1",
+		ImplementsResponses: false,
+	},
 }
 
 // GetProviderByName returns the provider configuration for a given name with O(1) lookup

internal/plugins/ai/perplexity/perplexity.go

@@ -4,9 +4,10 @@ import (
 	"context"
 	"fmt"
 	"os"
-	"sync" // Added sync package
+	"sync"
 
 	"github.com/danielmiessler/fabric/internal/domain"
+	debuglog "github.com/danielmiessler/fabric/internal/log"
 	"github.com/danielmiessler/fabric/internal/plugins"
 	perplexity "github.com/sgaunet/perplexity-go/v2"
 
@@ -171,7 +172,7 @@ func (c *Client) SendStream(msgs []*chat.ChatCompletionMessage, opts *domain.Cha
 		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
+			debuglog.Log("perplexity streaming error: %v\n", err)
 			// 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.

internal/plugins/ai/vendors.go

@@ -148,7 +148,6 @@ func (o *VendorsManager) setupVendorTo(vendor Vendor, configuredVendors map[stri
 		delete(configuredVendors, vendor.GetName())
 		fmt.Printf("[%v] skipped\n", vendor.GetName())
 	}
-	return
 }
 
 type modelResult struct {

internal/plugins/db/fsdb/patterns.go

@@ -31,6 +31,27 @@ type Pattern struct {
 func (o *PatternsEntity) GetApplyVariables(
 	source string, variables map[string]string, input string) (pattern *Pattern, err error) {
 
+	if pattern, err = o.loadPattern(source); err != nil {
+		return
+	}
+
+	err = o.applyVariables(pattern, variables, input)
+	return
+}
+
+// GetWithoutVariables returns a pattern with only the {{input}} placeholder processed
+// and skips template variable replacement
+func (o *PatternsEntity) GetWithoutVariables(source, input string) (pattern *Pattern, err error) {
+
+	if pattern, err = o.loadPattern(source); err != nil {
+		return
+	}
+
+	o.applyInput(pattern, input)
+	return
+}
+
+func (o *PatternsEntity) loadPattern(source string) (pattern *Pattern, err error) {
 	// Determine if this is a file path
 	isFilePath := strings.HasPrefix(source, "\\") ||
 		strings.HasPrefix(source, "/") ||
@@ -39,8 +60,8 @@ func (o *PatternsEntity) GetApplyVariables(
 
 	if isFilePath {
 		// Resolve the file path using GetAbsolutePath
-		absPath, err := util.GetAbsolutePath(source)
-		if err != nil {
+		var absPath string
+		if absPath, err = util.GetAbsolutePath(source); err != nil {
 			return nil, fmt.Errorf("could not resolve file path: %v", err)
 		}
 
@@ -51,26 +72,27 @@ func (o *PatternsEntity) GetApplyVariables(
 		pattern, err = o.getFromDB(source)
 	}
 
-	if err != nil {
-		return
-	}
-
-	// Apply variables to the pattern
-	err = o.applyVariables(pattern, variables, input)
 	return
 }
 
-func (o *PatternsEntity) applyVariables(
-	pattern *Pattern, variables map[string]string, input string) (err error) {
-
-	// Ensure pattern has an {{input}} placeholder
-	// If not present, append it on a new line
+func (o *PatternsEntity) ensureInput(pattern *Pattern) {
 	if !strings.Contains(pattern.Pattern, "{{input}}") {
 		if !strings.HasSuffix(pattern.Pattern, "\n") {
 			pattern.Pattern += "\n"
 		}
 		pattern.Pattern += "{{input}}"
 	}
+}
+
+func (o *PatternsEntity) applyInput(pattern *Pattern, input string) {
+	o.ensureInput(pattern)
+	pattern.Pattern = strings.ReplaceAll(pattern.Pattern, "{{input}}", input)
+}
+
+func (o *PatternsEntity) applyVariables(
+	pattern *Pattern, variables map[string]string, input string) (err error) {
+
+	o.ensureInput(pattern)
 
 	// Temporarily replace {{input}} with a sentinel token to protect it
 	// from recursive variable resolution

internal/plugins/db/fsdb/patterns_test.go

@@ -145,6 +145,22 @@ func TestGetApplyVariables(t *testing.T) {
 	}
 }
 
+func TestGetWithoutVariables(t *testing.T) {
+	entity, cleanup := setupTestPatternsEntity(t)
+	defer cleanup()
+
+	createTestPattern(t, entity, "test-pattern", "Prefix {{input}} {{roam}}")
+
+	result, err := entity.GetWithoutVariables("test-pattern", "hello")
+	require.NoError(t, err)
+	assert.Equal(t, "Prefix hello {{roam}}", result.Pattern)
+
+	createTestPattern(t, entity, "no-input", "Static content")
+	result, err = entity.GetWithoutVariables("no-input", "hi")
+	require.NoError(t, err)
+	assert.Equal(t, "Static content\nhi", result.Pattern)
+}
+
 func TestPatternsEntity_Save(t *testing.T) {
 	entity, cleanup := setupTestPatternsEntity(t)
 	defer cleanup()

internal/plugins/template/extension_registry.go

@@ -10,8 +10,9 @@ import (
 	"strings"
 	"time"
 
+	debuglog "github.com/danielmiessler/fabric/internal/log"
+
 	"gopkg.in/yaml.v3"
-	// Add this import
 )
 
 // ExtensionDefinition represents a single extension configuration
@@ -87,9 +88,7 @@ func NewExtensionRegistry(configDir string) *ExtensionRegistry {
 	r.ensureConfigDir()
 
 	if err := r.loadRegistry(); err != nil {
-		if Debug {
-			fmt.Printf("Warning: could not load extension registry: %v\n", err)
-		}
+		debuglog.Log("Warning: could not load extension registry: %v\n", err)
 	}
 
 	return r

internal/plugins/template/template.go

@@ -6,6 +6,8 @@ import (
 	"path/filepath"
 	"regexp"
 	"strings"
+
+	debuglog "github.com/danielmiessler/fabric/internal/log"
 )
 
 var (
@@ -14,7 +16,6 @@ var (
 	filePlugin     = &FilePlugin{}
 	fetchPlugin    = &FetchPlugin{}
 	sysPlugin      = &SysPlugin{}
-	Debug          = false // Debug flag
 )
 
 var extensionManager *ExtensionManager
@@ -33,9 +34,7 @@ var pluginPattern = regexp.MustCompile(`\{\{plugin:([^:]+):([^:]+)(?::([^}]+))?\
 var extensionPattern = regexp.MustCompile(`\{\{ext:([^:]+):([^:]+)(?::([^}]+))?\}\}`)
 
 func debugf(format string, a ...interface{}) {
-	if Debug {
-		fmt.Printf(format, a...)
-	}
+	debuglog.Debug(debuglog.Trace, format, a...)
 }
 
 func ApplyTemplate(content string, variables map[string]string, input string) (string, error) {

internal/server/chat.go

@@ -130,6 +130,7 @@ func (h *ChatHandler) HandleChat(c *gin.Context) {
 					TopP:             request.TopP,
 					FrequencyPenalty: request.FrequencyPenalty,
 					PresencePenalty:  request.PresencePenalty,
+					Thinking:         request.Thinking,
 				}
 
 				session, err := chatter.Send(chatReq, opts)

internal/tools/patterns_loader.go

@@ -7,6 +7,7 @@ import (
 	"sort"
 	"strings"
 
+	debuglog "github.com/danielmiessler/fabric/internal/log"
 	"github.com/danielmiessler/fabric/internal/plugins"
 	"github.com/danielmiessler/fabric/internal/plugins/db/fsdb"
 	"github.com/danielmiessler/fabric/internal/tools/githelper"
@@ -335,9 +336,9 @@ func (o *PatternsLoader) createUniquePatternsFile() (err error) {
 					patternNamesMap[entry.Name()] = true
 				}
 			}
-			fmt.Fprintf(os.Stderr, "📂 Also included patterns from custom directory: %s\n", o.Patterns.CustomPatternsDir)
+			debuglog.Log("📂 Also included patterns from custom directory: %s\n", o.Patterns.CustomPatternsDir)
 		} else {
-			fmt.Fprintf(os.Stderr, "Warning: Could not read custom patterns directory %s: %v\n", o.Patterns.CustomPatternsDir, customErr)
+			debuglog.Log("Warning: Could not read custom patterns directory %s: %v\n", o.Patterns.CustomPatternsDir, customErr)
 		}
 	}
 

internal/tools/youtube/youtube.go

@@ -181,7 +181,8 @@ func (o *YouTube) tryMethodYtDlpInternal(videoId string, language string, additi
 		if len(langMatch) > 2 {
 			langMatch = langMatch[:2]
 		}
-		args = append(args, "--sub-langs", langMatch)
+		langOpts := language + "," + langMatch + ".*," + langMatch
+		args = append(args, "--sub-langs", langOpts)
 	}
 
 	// Add user-provided arguments last so they take precedence

nix/pkgs/fabric/gomod2nix.toml

@@ -26,8 +26,8 @@ schema = 3
     version = "v1.3.3"
     hash = "sha256-jv7ZshpSd7FZzKKN6hqlUgiR8C3y85zNIS/hq7g76Ho="
   [mod."github.com/anthropics/anthropic-sdk-go"]
-    version = "v1.7.0"
-    hash = "sha256-DvpFXlUE04HeMbqQX4HIC/KMJYPXJ8rEaZkNJb1rWxs="
+    version = "v1.9.1"
+    hash = "sha256-1saDnM1DMnDLHT4RoA/EFuOvW7CIFh2tkfOJ1/+itNc="
   [mod."github.com/araddon/dateparse"]
     version = "v0.0.0-20210429162001-6b43995a97de"
     hash = "sha256-UuX84naeRGMsFOgIgRoBHG5sNy1CzBkWPKmd6VbLwFw="
@@ -224,8 +224,8 @@ schema = 3
     version = "v1.0.2"
     hash = "sha256-+W9EIW7okXIXjWEgOaMh58eLvBZ7OshW2EhaIpNLSBU="
   [mod."github.com/ollama/ollama"]
-    version = "v0.9.0"
-    hash = "sha256-r2eU+kMG3tuJy2B43RXsfmeltzM9t05NEmNiJAW5qr4="
+    version = "v0.11.7"
+    hash = "sha256-3Wn1JWmil0aQQ2I/r398HbnUsi8ADoroqNyPziuxn/c="
   [mod."github.com/openai/openai-go"]
     version = "v1.8.2"
     hash = "sha256-O8aV3zEj6o8kIlzlkYaTW4RzvwR3qNUBYiN8SuTM1R0="
@@ -308,8 +308,8 @@ schema = 3
     version = "v0.18.0"
     hash = "sha256-tUpUPERjmRi7zldj0oPlnbnBhEkcI9iQGvP1HqlsK10="
   [mod."golang.org/x/crypto"]
-    version = "v0.39.0"
-    hash = "sha256-FtwjbVoAhZkx7F2hmzi9Y0J87CVVhWcrZzun+zWQLzc="
+    version = "v0.40.0"
+    hash = "sha256-I6p2fqvz63P9MwAuoQrljI7IUbfZQvCem0ii4Q2zZng="
   [mod."golang.org/x/exp"]
     version = "v0.0.0-20250531010427-b6e5de432a8b"
     hash = "sha256-QaFfjyB+pogCkUkJskR9xnXwkCOU828XJRrzwwLm6Ms="

nix/pkgs/fabric/version.nix

@@ -1 +1 @@
-"1.4.283"
+"1.4.306"

scripts/docker-test/README.md

@@ -1,116 +0,0 @@
-# Docker Test Environment for API Configuration Fix
-
-This directory contains a Docker-based testing setup for fixing the issue where Fabric calls Ollama and Bedrock APIs even when not configured. This addresses the problem where unconfigured services show error messages during model listing.
-
-## Quick Start
-
-```bash
-# Run all tests
-./scripts/docker-test/test-runner.sh
-
-# Interactive mode - pick which test to run
-./scripts/docker-test/test-runner.sh -i
-
-# Run specific test case
-./scripts/docker-test/test-runner.sh gemini-only
-
-# Shell into test environment
-./scripts/docker-test/test-runner.sh -s gemini-only
-
-# Build image only (for development)
-./scripts/docker-test/test-runner.sh -b
-
-# Show help
-./scripts/docker-test/test-runner.sh -h
-```
-
-## Test Cases
-
-1. **no-config**: No APIs configured
-2. **gemini-only**: Only Gemini configured (reproduces original issue #1195)
-3. **openai-only**: Only OpenAI configured
-4. **ollama-only**: Only Ollama configured
-5. **bedrock-only**: Only Bedrock configured
-6. **mixed**: Multiple APIs configured (Gemini + OpenAI + Ollama)
-
-## Environment Files
-
-Each test case has a corresponding environment file in `scripts/docker-test/env/`:
-
-- `env.no-config` - Empty configuration
-- `env.gemini-only` - Only Gemini API key
-- `env.openai-only` - Only OpenAI API key
-- `env.ollama-only` - Only Ollama URL
-- `env.bedrock-only` - Only Bedrock configuration
-- `env.mixed` - Multiple API configurations
-
-These files are volume-mounted into the Docker container and persist changes made with `fabric -S`.
-
-## Interactive Mode & Shell Access
-
-The interactive mode (`-i`) provides several options:
-
-```text
-Available test cases:
-
-1) No APIs configured (no-config)
-2) Only Gemini configured (gemini-only)
-3) Only OpenAI configured (openai-only)
-4) Only Ollama configured (ollama-only)
-5) Only Bedrock configured (bedrock-only)
-6) Mixed configuration (mixed)
-7) Run all tests
-0) Exit
-
-Add '!' after number to shell into test environment (e.g., '1!' to shell into no-config)
-```
-
-### Shell Mode
-
-- Use `1!`, `2!`, etc. to shell into any test environment
-- Run `fabric -S` to configure APIs interactively
-- Run `fabric --listmodels` or `fabric -L` to test model listing
-- Changes persist in the environment files
-- Type `exit` to return to test runner
-
-## Expected Results
-
-**Before Fix:**
-
-- `no-config` and `gemini-only` tests show Ollama connection errors
-- Tests show Bedrock authentication errors when BEDROCK_AWS_REGION not set
-- Error: `Ollama Get "http://localhost:11434/api/tags": dial tcp...`
-- Error: `Bedrock failed to list foundation models...`
-
-**After Fix:**
-
-- Clean output with no error messages for unconfigured services
-- Only configured services appear in model listings
-- Ollama only initialized when `OLLAMA_API_URL` is set
-- Bedrock only initialized when `BEDROCK_AWS_REGION` is set
-
-## Implementation Details
-
-- **Volume-mounted configs**: Environment files are mounted to `/home/testuser/.config/fabric/.env`
-- **Persistent state**: Configuration changes survive between test runs
-- **Single Docker image**: Built once from `scripts/docker-test/base/Dockerfile`, reused for all tests
-- **Isolated environments**: Each test uses its own environment file
-- **Cross-platform**: Works on macOS, Linux, and Windows with Docker
-
-## Development Workflow
-
-1. Make code changes to fix API initialization logic
-2. Run `./scripts/docker-test/test-runner.sh no-config` to test the main issue
-3. Use `./scripts/docker-test/test-runner.sh -i` for interactive testing
-4. Shell into environments (`1!`, `2!`, etc.) to debug specific configurations
-5. Run all tests before submitting PR: `./scripts/docker-test/test-runner.sh`
-
-## Architecture
-
-The fix involves:
-
-1. **Ollama**: Override `IsConfigured()` method to check for `OLLAMA_API_URL` env var
-2. **Bedrock**: Modify `hasAWSCredentials()` to require `BEDROCK_AWS_REGION`
-3. **Plugin Registry**: Only initialize providers when properly configured
-
-This prevents unnecessary API calls and eliminates confusing error messages for users.

scripts/docker-test/base/Dockerfile

@@ -1,30 +0,0 @@
-FROM golang:1.24-alpine AS builder
-
-WORKDIR /app
-COPY go.mod go.sum ./
-RUN go mod download
-
-COPY ./cmd/fabric ./cmd/fabric
-COPY ./internal ./internal
-RUN go build -o fabric ./cmd/fabric
-
-FROM alpine:latest
-RUN apk --no-cache add ca-certificates
-
-# Create a test user
-RUN adduser -D -s /bin/sh testuser
-
-# Switch to test user
-USER testuser
-WORKDIR /home/testuser
-
-# Set environment variables for the test user
-ENV HOME=/home/testuser
-ENV USER=testuser
-
-COPY --from=builder /app/fabric .
-
-# Create fabric config directory and empty .env file
-RUN mkdir -p .config/fabric && touch .config/fabric/.env
-
-ENTRYPOINT ["./fabric"]

scripts/docker-test/test-runner.sh

@@ -1,235 +0,0 @@
-#!/usr/bin/env bash
-
-set -e
-
-# Get the directory where this script is located
-top_dir="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
-base_name="$(basename "$top_dir")"
-cd "$top_dir"/../.. || exit 1
-
-# Check if bash version supports associative arrays
-if [[ ${BASH_VERSION%%.*} -lt 4 ]]; then
-    echo "This script requires bash 4.0 or later for associative arrays."
-    echo "Current version: $BASH_VERSION"
-    exit 1
-fi
-
-IMAGE_NAME="fabric-test-setup"
-ENV_DIR="scripts/${base_name}/env"
-
-# Test case descriptions
-declare -A test_descriptions=(
-    ["no-config"]="No APIs configured"
-    ["gemini-only"]="Only Gemini configured (reproduces original issue)"
-    ["openai-only"]="Only OpenAI configured"
-    ["ollama-only"]="Only Ollama configured"
-    ["bedrock-only"]="Only Bedrock configured"
-    ["mixed"]="Mixed configuration (Gemini + OpenAI + Ollama)"
-)
-
-# Test case order for consistent display
-test_order=("no-config" "gemini-only" "openai-only" "ollama-only" "bedrock-only" "mixed")
-
-build_image() {
-    echo "=== Building Docker image ==="
-    docker build -f "${top_dir}/base/Dockerfile" -t "$IMAGE_NAME" .
-    echo
-}
-
-check_env_file() {
-    local test_name="$1"
-    local env_file="$ENV_DIR/env.$test_name"
-
-    if [[ ! -f "$env_file" ]]; then
-        echo "Error: Environment file not found: $env_file"
-        exit 1
-    fi
-}
-
-run_test() {
-    local test_name="$1"
-    local description="${test_descriptions[$test_name]}"
-    local env_file="$ENV_DIR/env.$test_name"
-
-    check_env_file "$test_name"
-
-    echo "===================="
-    echo "Test: $description"
-    echo "Config: $test_name"
-    echo "Env file: $env_file"
-    echo "===================="
-
-    echo "Running test..."
-    if docker run --rm \
-        -e HOME=/home/testuser \
-        -e USER=testuser \
-        -v "$(pwd)/$env_file:/home/testuser/.config/fabric/.env:ro" \
-        "$IMAGE_NAME" --listmodels 2>&1; then
-        echo "✅ Test completed"
-    else
-        echo "❌ Test failed"
-    fi
-    echo
-}
-
-shell_into_env() {
-    local test_name="$1"
-    local description="${test_descriptions[$test_name]}"
-    local env_file="$ENV_DIR/env.$test_name"
-
-    check_env_file "$test_name"
-
-    echo "===================="
-    echo "Shelling into: $description"
-    echo "Config: $test_name"
-    echo "Env file: $env_file"
-    echo "===================="
-    echo "You can now run 'fabric -S' to configure, or 'fabric --listmodels' or 'fabric -L' to test."
-    echo "Changes to .env will persist in $env_file"
-    echo "Type 'exit' to return to the test runner."
-    echo
-
-    docker run -it --rm \
-        -e HOME=/home/testuser \
-        -e USER=testuser \
-        -v "$(pwd)/$env_file:/home/testuser/.config/fabric/.env" \
-        --entrypoint=/bin/sh \
-        "$IMAGE_NAME"
-}
-
-interactive_mode() {
-    echo "=== Interactive Mode ==="
-    echo "Available test cases:"
-    echo
-    local i=1
-    local cases=()
-    for test_name in "${test_order[@]}"; do
-        echo "$i) ${test_descriptions[$test_name]} ($test_name)"
-        cases[i]="$test_name"
-        ((i++))
-    done
-    echo "$i) Run all tests"
-    echo "0) Exit"
-    echo
-    echo "Add '!' after number to shell into test environment (e.g., '1!' to shell into no-config)"
-    echo
-
-    while true; do
-        read -r -p "Select test case (0-$i) [or 1!, etc. to shell into test environment]: " choice
-
-        # Check for shell mode (! suffix)
-        local shell_mode=false
-        if [[ "$choice" == *"!" ]]; then
-            shell_mode=true
-            choice="${choice%!}"  # Remove the ! suffix
-        fi
-
-        if [[ "$choice" == "0" ]]; then
-            if [[ "$shell_mode" == true ]]; then
-                echo "Cannot shell into exit option."
-                continue
-            fi
-            echo "Exiting..."
-            exit 0
-        elif [[ "$choice" == "$i" ]]; then
-            if [[ "$shell_mode" == true ]]; then
-                echo "Cannot shell into 'run all tests' option."
-                continue
-            fi
-            echo "Running all tests..."
-            run_all_tests
-            break
-        elif [[ "$choice" -ge 1 && "$choice" -lt "$i" ]]; then
-            local selected_test="${cases[$choice]}"
-            if [[ "$shell_mode" == true ]]; then
-                echo "Shelling into: ${test_descriptions[$selected_test]}"
-                shell_into_env "$selected_test"
-            else
-                echo "Running: ${test_descriptions[$selected_test]}"
-                run_test "$selected_test"
-            fi
-
-            read -r -p "Continue testing? (y/n): " again
-            if [[ "$again" != "y" && "$again" != "Y" ]]; then
-                break
-            fi
-            echo
-        else
-            echo "Invalid choice. Please select 0-$i (optionally with '!' for shell mode)."
-        fi
-    done
-}
-
-run_all_tests() {
-    echo "=== Testing PR #1645: Conditional API initialization ==="
-    echo
-
-    for test_name in "${test_order[@]}"; do
-        run_test "$test_name"
-    done
-
-    echo "=== Test run complete ==="
-    echo "Review the output above to check:"
-    echo "1. No Ollama connection errors when OLLAMA_URL not set"
-    echo "2. No Bedrock authentication errors when BEDROCK_AWS_REGION not set"
-    echo "3. Only configured services appear in model listings"
-}
-
-show_help() {
-    echo "Usage: $0 [OPTIONS] [TEST_CASE]"
-    echo
-    echo "Test PR #1645 conditional API initialization"
-    echo
-    echo "Options:"
-    echo "  -h, --help       Show this help message"
-    echo "  -i, --interactive Run in interactive mode"
-    echo "  -b, --build-only  Build image only, don't run tests"
-    echo "  -s, --shell TEST  Shell into test environment"
-    echo
-    echo "Test cases:"
-    for test_name in "${test_order[@]}"; do
-        echo "  $test_name: ${test_descriptions[$test_name]}"
-    done
-    echo
-    echo "Examples:"
-    echo "  $0                    # Run all tests"
-    echo "  $0 -i                 # Interactive mode"
-    echo "  $0 gemini-only        # Run specific test"
-    echo "  $0 -s gemini-only     # Shell into gemini-only environment"
-    echo "  $0 -b                 # Build image only"
-    echo
-    echo "Environment files are located in $ENV_DIR/ and can be edited directly."
-}
-
-# Parse command line arguments
-if [[ $# -eq 0 ]]; then
-    build_image
-    run_all_tests
-elif [[ "$1" == "-h" || "$1" == "--help" ]]; then
-    show_help
-elif [[ "$1" == "-i" || "$1" == "--interactive" ]]; then
-    build_image
-    interactive_mode
-elif [[ "$1" == "-b" || "$1" == "--build-only" ]]; then
-    build_image
-elif [[ "$1" == "-s" || "$1" == "--shell" ]]; then
-    if [[ -z "$2" ]]; then
-        echo "Error: -s/--shell requires a test case name"
-        echo "Use -h for help."
-        exit 1
-    fi
-    if [[ -z "${test_descriptions[$2]}" ]]; then
-        echo "Error: Unknown test case: $2"
-        echo "Use -h for help."
-        exit 1
-    fi
-    build_image
-    shell_into_env "$2"
-elif [[ -n "${test_descriptions[$1]}" ]]; then
-    build_image
-    run_test "$1"
-else
-    echo "Unknown test case or option: $1"
-    echo "Use -h for help."
-    exit 1
-fi

scripts/docker/Dockerfile

@@ -1,41 +1,28 @@
-# Use official golang image as builder
-FROM golang:1.24.2-alpine AS builder
+# syntax=docker/dockerfile:1
 
-# Set working directory
-WORKDIR /app
+FROM golang:1.24-alpine AS builder
+
+WORKDIR /src
+
+# Install build dependencies
+RUN apk add --no-cache git
 
-# Copy go mod and sum files
 COPY go.mod go.sum ./
-
-# Download dependencies
 RUN go mod download
 
-# Copy source code
 COPY . .
 
-# Build the application
-RUN CGO_ENABLED=0 GOOS=linux go build -o fabric ./cmd/fabric
+RUN CGO_ENABLED=0 GOOS=linux go build -ldflags="-s -w" -o /fabric ./cmd/fabric
 
-# Use scratch as final base image
 FROM alpine:latest
 
-# Copy the binary from builder
-COPY --from=builder /app/fabric /fabric
+LABEL org.opencontainers.image.description="A Docker image for running the Fabric CLI. See https://github.com/danielmiessler/Fabric/tree/main/scripts/docker for details."
 
-# Copy patterns directory
-COPY patterns /patterns
+RUN apk add --no-cache ca-certificates \
+    && mkdir -p /root/.config/fabric
 
-# Ensure clean config directory and copy ENV file
-RUN rm -rf /root/.config/fabric && \
-    mkdir -p /root/.config/fabric
-COPY ENV /root/.config/fabric/.env
+COPY --from=builder /fabric /usr/local/bin/fabric
 
-# Add debug commands
-RUN ls -la /root/.config/fabric/
-
-# Expose port 8080
 EXPOSE 8080
 
-# Run the binary with debug output
-ENTRYPOINT ["/fabric"]
-CMD ["--serve"] 
+ENTRYPOINT ["fabric"]

scripts/docker/README.md

@@ -1,40 +1,60 @@
-# Docker Deployment
+# Fabric Docker Image
 
-This directory contains Docker configuration files for running Fabric in containers.
+This directory provides a simple Docker setup for running the [Fabric](https://github.com/danielmiessler/fabric) CLI.
 
-## Files
+## Build
 
-- `Dockerfile` - Main Docker build configuration
-- `docker-compose.yml` - Docker Compose stack configuration  
-- `start-docker.sh` - Helper script to start the stack
-- `README.md` - This documentation
-
-## Quick Start
+Build the image from the repository root:
 
 ```bash
-# Start the Docker stack
-./start-docker.sh
-
-# Or manually with docker-compose
-docker-compose up -d
-
-# View logs
-docker-compose logs -f
-
-# Stop the stack
-docker-compose down
+docker build -t fabric -f scripts/docker/Dockerfile .
 ```
 
-## Building
+## Persisting configuration
+
+Fabric stores its configuration in `~/.config/fabric/.env`. Mount this path to keep your settings on the host.
+
+### Using a host directory
 
 ```bash
-# Build the Docker image
-docker build -t fabric .
-
-# Or use docker-compose
-docker-compose build
+mkdir -p $HOME/.fabric-config
+# Run setup to create the .env and download patterns
+ docker run --rm -it -v $HOME/.fabric-config:/root/.config/fabric fabric --setup
 ```
 
-## Configuration
+Subsequent runs can reuse the same directory:
 
-Make sure to configure your environment variables and API keys before running the Docker stack. See the main README.md for setup instructions.
+```bash
+docker run --rm -it -v $HOME/.fabric-config:/root/.config/fabric fabric -p your-pattern
+```
+
+### Mounting a single .env file
+
+If you only want to persist the `.env` file:
+
+```bash
+# assuming .env exists in the current directory
+docker run --rm -it -v $PWD/.env:/root/.config/fabric/.env fabric -p your-pattern
+```
+
+## Running the server
+
+Expose port 8080 to use Fabric's REST API:
+
+```bash
+docker run --rm -it -p 8080:8080 -v $HOME/.fabric-config:/root/.config/fabric fabric --serve
+```
+
+The API will be available at `http://localhost:8080`.
+
+## Multi-arch builds and GHCR packages
+
+For multi-arch Docker builds (such as those used for GitHub Container Registry packages), the description should be set via annotations in the manifest instead of the Dockerfile LABEL. When building multi-arch images, ensure the build configuration includes:
+
+```json
+"annotations": {
+  "org.opencontainers.image.description": "A Docker image for running the Fabric CLI. See https://github.com/danielmiessler/Fabric/tree/main/scripts/docker for details."
+}
+```
+
+This ensures that GHCR packages display the proper description.

scripts/docker/docker-compose.yml

@@ -1,11 +0,0 @@
-version: '3.8'
-
-services:
-  fabric-api:
-    build: .
-    ports:
-      - "8080:8080"
-    volumes:
-      - ./ENV:/root/.config/fabric/.env:ro
-    environment:
-      - GIN_MODE=release 

scripts/docker/start-docker.sh

@@ -1,11 +0,0 @@
-#!/bin/bash
-
-# Helper script to start the Fabric Docker stack
-
-echo "Starting Fabric Docker stack..."
-cd "$(dirname "$0")"
-docker-compose up -d
-
-echo "Fabric is now running!"
-echo "Check logs with: docker-compose logs -f"
-echo "Stop with: docker-compose down"

scripts/pattern_descriptions/pattern_descriptions.json

@@ -1332,14 +1332,6 @@
         "DEVELOPMENT"
       ]
     },
-    {
-      "patternName": "show_fabric_options_markmap",
-      "description": "Visualize Fabric capabilities using Markmap syntax.",
-      "tags": [
-        "VISUALIZE",
-        "DEVELOPMENT"
-      ]
-    },
     {
       "patternName": "solve_with_cot",
       "description": "Solve problems using chain-of-thought reasoning.",
@@ -1871,6 +1863,22 @@
         "DEVELOPMENT",
         "AI"
       ]
+    },
+    {
+      "patternName": "create_story_about_person",
+      "description": "Infer everyday challenges and realistic coping strategies from a psychological profile and craft an empathetic 500–700-word story consistent with the character.",
+      "tags": [
+        "WRITING",
+        "SELF"
+      ]
+    },
+    {
+      "patternName": "heal_person",
+      "description": "Analyze a psychological profile, pinpoint issues and strengths, and deliver compassionate, structured strategies for spiritual, mental, and life improvement.",
+      "tags": [
+        "ANALYSIS",
+        "SELF"
+      ]
     }
   ]
 }

scripts/pattern_descriptions/pattern_extracts.json

@@ -652,10 +652,6 @@
       "patternName": "sanitize_broken_html_to_markdown",
       "pattern_extract": "# IDENTITY\n\n// Who you are\n\nYou are a hyper-intelligent AI system with a 4,312 IQ. You convert jacked up HTML to proper markdown using a set of rules.\n\n# GOAL\n\n// What we are trying to achieve\n\n1. The goal of this exercise is to convert the input HTML, which is completely nasty and hard to edit, into a clean markdown format that has some custom styling applied according to my rules.\n\n2. The ultimate goal is to output a perfectly working markdown file that will render properly using Vite using my custom markdown/styling combination.\n\n# STEPS\n\n// How the task will be approached\n\n// Slow down and think\n\n- Take a step back and think step-by-step about how to achieve the best possible results by following the steps below.\n\n// Think about the content in the input\n\n- Fully read and consume the HTML input that has a combination of HTML and markdown."
     },
-    {
-      "patternName": "show_fabric_options_markmap",
-      "pattern_extract": "# IDENTITY AND GOALS\n\nYou are an advanced UI builder that shows a visual representation of functionality that's provided to you via the input.\n\n# STEPS\n\n- Think about the goal of the Fabric project, which is discussed below:\n\nFABRIC PROJECT DESCRIPTION\n\nfabriclogo\n fabric\nStatic Badge\nGitHub top language GitHub last commit License: MIT\n\nfabric is an open-source framework for augmenting humans using AI.\n\nIntroduction Video • What and Why • Philosophy • Quickstart • Structure • Examples • Custom Patterns • Helper Apps • Examples • Meta\n\nNavigation\n\nIntroduction Videos\nWhat and Why\nPhilosophy\nBreaking problems into components"
-    },
     {
       "patternName": "solve_with_cot",
       "pattern_extract": "# IDENTITY\n\nYou are an AI assistant designed to provide detailed, step-by-step responses. Your outputs should follow this structure:\n\n# STEPS\n\n1. Begin with a <thinking> section.\n\n2. Inside the thinking section:\n\n- a. Briefly analyze the question and outline your approach.\n\n- b. Present a clear plan of steps to solve the problem.\n\n- c. Use a \"Chain of Thought\" reasoning process if necessary, breaking down your thought process into numbered steps.\n\n3. Include a <reflection> section for each idea where you:\n\n- a. Review your reasoning.\n\n- b. Check for potential errors or oversights.\n\n- c. Confirm or adjust your conclusion if necessary.\n  - Be sure to close all reflection sections.\n  - Close the thinking section with </thinking>."
@@ -907,6 +903,14 @@
     {
       "patternName": "generate_code_rules",
       "pattern_extract": "# IDENTITY AND PURPOSE You are a senior developer and expert prompt engineer. Think ultra hard to distill the following transcription or tutorial in as little set of unique rules as possible intended for best practices guidance in AI assisted coding tools, each rule has to be in one sentence as a direct instruction, avoid explanations and cosmetic language. Output in Markdown, I prefer bullet dash (-). --- # TRANSCRIPT"
+    },
+    {
+      "patternName": "create_story_about_person",
+      "pattern_extract": "You are an expert creative writer specializing in character-driven narratives, and a keen observer of human psychology. Your task is to craft a compelling, realistic short story based on a psychological profile or personal data provided by the user. **Input:** The user will provide a psychological profile or descriptive data about a fictional or real person. This input will be clearly delimited by triple backticks (```). It may include personality traits, habits, fears, motivations, strengths, weaknesses, background information, or specific behavioral patterns. **Task Steps:** 1. **Analyze Profile:** Carefully read and internalize the provided psychological profile. Identify the core personality traits, typical reactions, strengths, and vulnerabilities of the individual. 2. **Brainstorm Challenges:** Based on the analysis from Step 1, generate 3-5 common, relatable, everyday problems or minor dilemmas that a person with this specific profile might genuinely encounter. These challenges should be varied and could span social, professional, personal, or emotional domains. 3. **Develop Strategies:** For each identified problem from Step 2, devise 1-2 specific, plausible methods or strategies that the character, consistent with their psychological profile, would naturally employ (or attempt to employ) to navigate, cope with, or solve these challenges. Consider both internal thought processes and external actions. 4. **Construct Narrative:** Weave these problems and the character's responses into a cohesive, engaging short story (approximately 500-700 words, 3-5 paragraphs). The story should have a clear narrative flow, introducing the character, presenting the challenges, and showing their journey through them. 5. **Maintain Consistency:** Throughout the story, ensure the character's actions, dialogue, internal monologue, and emotional reactions are consistently aligned with the psychological profile provided. The story should feel authentic to the character. **Output Requirements:** * **Format:** A continuous narrative short story. * **Tone:** Empathetic, realistic, and engaging. * **Content:** The story must clearly depict the character facing everyday problems and demonstrate their unique methods and strategies for navigating these challenges, directly reflecting the input profile. * **Length:** Approximately 500-700 words. * **Avoid:** Overly dramatic or fantastical scenarios unless the profile explicitly suggests such a context. Focus on the 'everyday common problems'. **Example of Input Format:** ``` [Psychological Profile/Data Here] ```"
+    },
+    {
+      "patternName": "heal_person",
+      "pattern_extract": "# IDENTITY and PURPOSE You are an AI assistant whose primary responsibility is to interpret and analyze psychological profiles and/or psychology data files provided as input. Your role is to carefully process this data and use your expertise to develop a tailored plan aimed at spiritual and mental healing, as well as overall life improvement for the subject. You must approach each case with sensitivity, applying psychological knowledge and holistic strategies to create actionable, personalized recommendations that address both mental and spiritual well-being. Your focus is on structured, compassionate, and practical guidance that can help the individual make meaningful improvements in their life. Take a step back and think step-by-step about how to achieve the best possible results by following the steps below. # STEPS - Carefully review the psychological-profile and/or psychology data file provided as input. - Analyze the data to identify key issues, strengths, and areas needing improvement related to the subject's mental and spiritual well-being. - Develop a comprehensive plan that includes specific strategies for spiritual healing, mental health improvement, and overall life enhancement. - Structure your output to clearly outline recommendations, resources, and actionable steps tailored to the individual's unique profile. # OUTPUT INSTRUCTIONS - Only output Markdown. - Ensure your output is organized, clear, and easy to follow, using headings, subheadings, and bullet points where appropriate. - Ensure you follow ALL these instructions when creating your output. # INPUT INPUT:# IDENTITY and PURPOSE You are an AI assistant whose primary responsibility is to interpret and analyze psychological profiles and/or psychology data files provided as input. Your role is to carefully process this data and use your expertise to develop a tailored plan aimed at spiritual and mental healing, as well as overall life improvement for the subject. You must approach each case with sensitivity, applying psychological knowledge and holistic strategies to create actionable, personalized recommendations that address both mental and spiritual well-being. Your focus is on structured, compassionate, and practical guidance that can help the individual make meaningful improvements in their life. Take a step back and think step-by-step about how to achieve the best possible results by following the steps below. # STEPS - Carefully review the psychological-profile and/or psychology data file provided as input. - Analyze the data to identify key issues, strengths, and areas needing improvement related to the subject's mental and spiritual well-being. - Develop a comprehensive plan that includes specific strategies for spiritual healing, mental health improvement, and overall life enhancement. - Structure your output to clearly outline recommendations, resources, and actionable steps tailored to the individual's unique profile. # OUTPUT INSTRUCTIONS - Only output Markdown. - Ensure your output is organized, clear, and easy to follow, using headings, subheadings, and bullet points where appropriate. - Ensure you follow ALL these instructions when creating your output. # INPUT INPUT:"
     }
   ]
 }

scripts/readme_updates/README.md

@@ -0,0 +1,99 @@
+# README Update Scripts
+
+This directory contains automation scripts for updating the main README.md file with release information from the changelog database.
+
+## `update_readme_features.py`
+
+A Python script that generates the "Recent Major Features" section for the README by extracting and filtering release information from the changelog SQLite database.
+
+### Usage
+
+```bash
+# Generate the Recent Major Features section with default limit (20 releases)
+python scripts/readme_updates/update_readme_features.py
+
+# Specify a custom limit
+python scripts/readme_updates/update_readme_features.py --limit 15
+
+# Use a custom database path
+python scripts/readme_updates/update_readme_features.py --db /path/to/changelog.db
+```
+
+### How It Works
+
+1. **Database Connection**: Connects to `cmd/generate_changelog/changelog.db` (or custom path)
+2. **Data Extraction**: Queries the `versions` table for release information
+3. **Feature Filtering**: Uses heuristics to identify feature/improvement releases
+4. **Markdown Generation**: Formats output to match README style
+
+### Feature Detection Heuristics
+
+The script uses keyword-based heuristics to filter releases:
+
+#### Include Keywords (Features/Improvements)
+- new, feature, feat, add, introduce, enable, support
+- improve, enhance, performance, speed
+- option, flag, argument, parameter
+- integration, provider, search, tts, audio, model
+- cli, ui, web, oauth, sync, database
+- notifications, desktop, reasoning, thinking
+
+#### Exclude Keywords (Non-Features)
+- fix, bug, hotfix
+- ci, cd, pipeline, chore
+- docs, readme, refactor, style, typo
+- test, bump, deps, dependency
+- merge, revert, format, lint, build
+- release, prepare, coverage, security
+
+### Integration with README
+
+To update the README with new release features:
+
+```bash
+# Generate the features and save to a temporary file
+python scripts/readme_updates/update_readme_features.py --limit 20 > /tmp/recent_features.md
+
+# Manually replace the "### Recent Major Features" section in README.md
+# with the generated content
+```
+
+### Database Schema
+
+The script expects the following SQLite table structure:
+
+```sql
+CREATE TABLE versions (
+    name TEXT PRIMARY KEY,
+    date DATETIME,
+    commit_sha TEXT,
+    pr_numbers TEXT,
+    ai_summary TEXT,
+    created_at DATETIME DEFAULT CURRENT_TIMESTAMP
+);
+```
+
+### Date Format Support
+
+The script can parse various date formats:
+- ISO 8601 with timezone: `2025-08-14 14:11:04+00:00`
+- ISO 8601 basic: `2025-08-14T14:11:04`
+- Date only: `2025-08-14`
+- US format: `08/14/2025`
+
+Output format is standardized to: `Aug 14, 2025`
+
+### Maintenance Notes
+
+- **AI Summary Format Changes**: If the format of AI summaries changes, update the `extract_title_desc()` and `split_summary()` functions
+- **Keyword Tuning**: Adjust `INCLUDE_RE` and `EXCLUDE_RE` patterns as needed
+- **Title Extraction**: The script attempts to extract concise titles from feature descriptions
+- **Description Length**: Descriptions are limited to 200 characters for readability
+
+### Future Enhancements
+
+Potential improvements for automated README updates:
+- Add section delimiter markers in README for automated replacement
+- Create a GitHub Action to run on new releases
+- Add support for categorizing features by type
+- Implement confidence scoring for feature detection

scripts/readme_updates/update_readme_features.py

@@ -0,0 +1,281 @@
+#!/usr/bin/env python3
+"""
+Generate the '### Recent Major Features' markdown section for README from the changelog SQLite DB.
+
+- Connects to cmd/generate_changelog/changelog.db
+- Extracts version, date, and AI summaries from the 'versions' table
+- Heuristically filters for feature/improvement items (excludes CI/CD/docs/bug fixes)
+- Formats output to match README style:
+  - [vX.Y.Z](https://github.com/danielmiessler/fabric/releases/tag/vX.Y.Z) (Aug 14, 2025) — **Feature Name**: Short description
+
+Usage:
+  python scripts/readme_updates/update_readme_features.py --limit 20
+"""
+
+import argparse
+import sqlite3
+from pathlib import Path
+from datetime import datetime
+import re
+import sys
+from typing import List, Optional, Tuple
+
+# Heuristics for filtering feature-related lines
+EXCLUDE_RE = re.compile(
+    r"(?i)\b(fix|bug|hotfix|ci|cd|pipeline|chore|docs|doc|readme|refactor|style|typo|"
+    "test|tests|bump|deps|dependency|merge|revert|format|lint|build|release\b|prepare|"
+    "codeowners|coverage|security)\b"
+)
+INCLUDE_RE = re.compile(
+    r"(?i)\b(new|feature|feat|add|added|introduce|enable|support|improve|enhance|"
+    "performance|speed|option|flag|argument|parameter|integration|provider|search|tts|"
+    "audio|model|cli|ui|web|oauth|sync|database|notifications|desktop|reasoning|thinking)\b"
+)
+
+
+def parse_args():
+    """Parse command-line arguments."""
+    p = argparse.ArgumentParser(
+        description="Generate README 'Recent Major Features' markdown from changelog DB."
+    )
+    p.add_argument(
+        "--limit", type=int, default=20, help="Maximum number of releases to include."
+    )
+    p.add_argument(
+        "--db",
+        type=str,
+        default=None,
+        help="Optional path to changelog.db (defaults to repo cmd/generate_changelog/changelog.db)",
+    )
+    return p.parse_args()
+
+
+def repo_root() -> Path:
+    """Get the repository root directory."""
+    # scripts/readme_updates/update_readme_features.py -> repo root is parent.parent.parent
+    return Path(__file__).resolve().parent.parent.parent
+
+
+def db_path(args) -> Path:
+    """Determine the database path."""
+    if args.db:
+        return Path(args.db).expanduser().resolve()
+    return repo_root() / "cmd" / "generate_changelog" / "changelog.db"
+
+
+def connect(dbfile: Path):
+    """Connect to the SQLite database."""
+    if not dbfile.exists():
+        print(f"ERROR: changelog database not found: {dbfile}", file=sys.stderr)
+        sys.exit(1)
+    return sqlite3.connect(str(dbfile))
+
+
+def normalize_version(name: str) -> str:
+    """Ensure version string starts with 'v'."""
+    n = str(name).strip()
+    return n if n.startswith("v") else f"v{n}"
+
+
+def parse_date(value) -> str:
+    """Parse various date formats and return formatted string."""
+    if value is None:
+        return "(Unknown date)"
+
+    # Handle the ISO format with timezone from the database
+    s = str(value).strip()
+
+    # Try to parse the ISO format with timezone
+    if "+" in s or "T" in s:
+        # Remove timezone info and microseconds for simpler parsing
+        s_clean = s.split("+")[0].split(".")[0]
+        try:
+            dt = datetime.strptime(s_clean, "%Y-%m-%d %H:%M:%S")
+            return dt.strftime("%b %d, %Y").replace(" 0", " ")
+        except ValueError:
+            pass
+
+    # Fallback formats
+    fmts = [
+        "%Y-%m-%d",
+        "%Y-%m-%d %H:%M:%S",
+        "%Y-%m-%dT%H:%M:%S",
+        "%Y/%m/%d",
+        "%m/%d/%Y",
+    ]
+
+    for fmt in fmts:
+        try:
+            dt = datetime.strptime(s, fmt)
+            return dt.strftime("%b %d, %Y").replace(" 0", " ")
+        except ValueError:
+            continue
+
+    # Return original if we can't parse it
+    return f"({s})"
+
+
+def split_summary(text: str) -> List[str]:
+    """Split AI summary into individual lines/bullets."""
+    if not text:
+        return []
+
+    lines = []
+    # Split by newlines first
+    for line in text.split("\n"):
+        line = line.strip()
+        if not line:
+            continue
+        # Remove markdown headers
+        line = re.sub(r"^#+\s+", "", line)
+        # Remove PR links and author info
+        line = re.sub(
+            r"^PR\s+\[#\d+\]\([^)]+\)\s+by\s+\[[^\]]+\]\([^)]+\):\s*", "", line
+        )
+        # Remove bullet points
+        line = re.sub(r"^[-*•]\s+", "", line)
+        if line:
+            lines.append(line)
+
+    return lines
+
+
+def is_feature_line(line: str) -> bool:
+    """Check if a line describes a feature/improvement (not a bug fix or CI/CD)."""
+    line_lower = line.lower()
+
+    # Strong exclusions first
+    if any(
+        word in line_lower
+        for word in ["chore:", "fix:", "docs:", "test:", "ci:", "build:", "refactor:"]
+    ):
+        return False
+
+    if EXCLUDE_RE.search(line):
+        return False
+
+    return bool(INCLUDE_RE.search(line))
+
+
+def extract_title_desc(line: str) -> Tuple[str, str]:
+    """Extract title and description from a feature line."""
+    # Remove any markdown formatting
+    line = re.sub(r"\*\*([^*]+)\*\*", r"\1", line)
+
+    # Look for colon separator first
+    if ":" in line:
+        parts = line.split(":", 1)
+        if len(parts) == 2:
+            title = parts[0].strip()
+            desc = parts[1].strip()
+
+            # Clean up the title
+            title = (
+                title.replace("Introduce ", "")
+                .replace("Enable ", "")
+                .replace("Add ", "")
+            )
+            title = title.replace("Implement ", "").replace("Support ", "")
+
+            # Make title more concise
+            if len(title) > 30:
+                # Try to extract key words
+                key_words = []
+                for word in title.split():
+                    if word[0].isupper() or "-" in word or "_" in word:
+                        key_words.append(word)
+                if key_words:
+                    title = " ".join(key_words[:3])
+
+            return (title, desc)
+
+    # Fallback: use first sentence as description
+    sentences = re.split(r"[.!?]\s+", line)
+    if sentences:
+        desc = sentences[0].strip()
+        # Extract a title from the description
+        if "thinking" in desc.lower():
+            return ("AI Reasoning", desc)
+        elif "token" in desc.lower() and "context" in desc.lower():
+            return ("Extended Context", desc)
+        elif "curl" in desc.lower() or "install" in desc.lower():
+            return ("Easy Setup", desc)
+        elif "vendor" in desc.lower() or "model" in desc.lower():
+            return ("Model Management", desc)
+        elif "notification" in desc.lower():
+            return ("Desktop Notifications", desc)
+        elif "tts" in desc.lower() or "speech" in desc.lower():
+            return ("Text-to-Speech", desc)
+        elif "oauth" in desc.lower() or "auth" in desc.lower():
+            return ("OAuth Auto-Auth", desc)
+        elif "search" in desc.lower() and "web" in desc.lower():
+            return ("Web Search", desc)
+        else:
+            # Generic title from first significant words
+            words = desc.split()[:2]
+            title = " ".join(words)
+            return (title, desc)
+
+    return ("Feature", line)
+
+
+def pick_feature(ai_summary: str) -> Optional[Tuple[str, str]]:
+    """Pick the best feature line from the AI summary."""
+    lines = split_summary(ai_summary)
+
+    # Look for the first feature line
+    for line in lines:
+        if is_feature_line(line):
+            title, desc = extract_title_desc(line)
+            # Clean up description - remove redundant info
+            desc = desc[:200] if len(desc) > 200 else desc  # Limit length
+            return (title, desc)
+
+    return None
+
+
+def build_item(
+    version: str, date_str: str, feature_title: str, feature_desc: str
+) -> str:
+    """Build a markdown list item for a release."""
+    url = f"https://github.com/danielmiessler/fabric/releases/tag/{version}"
+    return f"- [{version}]({url}) ({date_str}) — **{feature_title}**: {feature_desc}"
+
+
+def main():
+    """Main function."""
+    args = parse_args()
+    dbfile = db_path(args)
+    conn = connect(dbfile)
+    cur = conn.cursor()
+
+    # Query the database
+    cur.execute("SELECT name, date, ai_summary FROM versions ORDER BY date DESC")
+    rows = cur.fetchall()
+
+    items = []
+    for name, date, summary in rows:
+        version = normalize_version(name)
+        date_fmt = parse_date(date)
+        feat = pick_feature(summary or "")
+
+        if not feat:
+            continue
+
+        title, desc = feat
+        items.append(build_item(version, date_fmt, title, desc))
+
+        if len(items) >= args.limit:
+            break
+
+    conn.close()
+
+    # Output the markdown
+    print("### Recent Major Features")
+    print()
+    for item in items:
+        print(item)
+
+
+if __name__ == "__main__":
+    main()

web/pnpm-lock.yaml

@@ -941,8 +941,8 @@ packages:
     resolution: {integrity: sha512-3UDv+G9CsCKO1WKMGw9fwq/SWJYbI0c5Y7LU1AXYoDdbhE2AHQ6N6Nb34sG8Fj7T5APy8qXDCKuuIHd1BR0tVA==}
     engines: {node: '>=8'}
 
-  devalue@5.1.1:
-    resolution: {integrity: sha512-maua5KUiapvEwiEAe+XnlZ3Rh0GD+qI1J/nb9vrJc3muPXvcF/8gXYTWF76+5DAqHyDUtOIImEuo0YKE9mshVw==}
+  devalue@5.3.2:
+    resolution: {integrity: sha512-UDsjUbpQn9kvm68slnrs+mfxwFkIflOhkanmyabZ8zOYk8SMEIbJ3TK+88g70hSIeytu4y18f0z/hYHMTrXIWw==}
 
   devlop@1.1.0:
     resolution: {integrity: sha512-RWmIqhcFf1lRYBvNmr7qTNuyCt/7/ns2jbpp1+PalgE/rDQcBT0fioSMUpJ93irlUhC5hrg4cYqe6U+0ImW0rA==}
@@ -2704,7 +2704,7 @@ snapshots:
       '@types/cookie': 0.6.0
       acorn: 8.14.1
       cookie: 1.0.2
-      devalue: 5.1.1
+      devalue: 5.3.2
       esm-env: 1.2.2
       kleur: 4.1.5
       magic-string: 0.30.17
@@ -3060,7 +3060,7 @@ snapshots:
   detect-libc@2.0.4:
     optional: true
 
-  devalue@5.1.1: {}
+  devalue@5.3.2: {}
 
   devlop@1.1.0:
     dependencies:

web/static/data/pattern_descriptions.json

@@ -1332,14 +1332,6 @@
         "DEVELOPMENT"
       ]
     },
-    {
-      "patternName": "show_fabric_options_markmap",
-      "description": "Visualize Fabric capabilities using Markmap syntax.",
-      "tags": [
-        "VISUALIZE",
-        "DEVELOPMENT"
-      ]
-    },
     {
       "patternName": "solve_with_cot",
       "description": "Solve problems using chain-of-thought reasoning.",
@@ -1871,6 +1863,22 @@
         "DEVELOPMENT",
         "AI"
       ]
+    },
+    {
+      "patternName": "create_story_about_person",
+      "description": "Infer everyday challenges and realistic coping strategies from a psychological profile and craft an empathetic 500–700-word story consistent with the character.",
+      "tags": [
+        "WRITING",
+        "SELF"
+      ]
+    },
+    {
+      "patternName": "heal_person",
+      "description": "Analyze a psychological profile, pinpoint issues and strengths, and deliver compassionate, structured strategies for spiritual, mental, and life improvement.",
+      "tags": [
+        "ANALYSIS",
+        "SELF"
+      ]
     }
   ]
 }