mirror of
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8be3c88711
This PR adds a collection of pre-built store agents that can be loaded into test databases for development and testing purposes. ### Changes 🏗️ - Add 17 exported agent JSON files in `backend/agents/` directory - Add `StoreAgent_rows.csv` containing store listing metadata (titles, descriptions, categories, images) - Add `load_store_agents.py` script to load agents into the test database - Add `load-store-agents` Makefile target for easy execution **Included Agents:** - Flux AI Image Generator - YouTube Transcription Scraper - Decision Maker Lead Finder - Smart Meeting Prep - Automated Support Agent - Unspirational Poster Maker - AI Video Generator - Automated SEO Blog Writer - Lead Finder (Local Businesses) - LinkedIn Post Generator - YouTube to LinkedIn Post Converter - Personal Newsletter - Email Scout - Contact Finder Assistant - YouTube Video to SEO Blog Writer - AI Webpage Copy Improver - Domain Name Finder - AI Function ### Checklist 📋 #### For code changes: - [x] I have clearly listed my changes in the PR description - [x] I have made a test plan - [x] I have tested my changes according to the test plan: - [x] Run `make load-store-agents` and verify agents are loaded into the database - [x] Verify store listings appear correctly with metadata from CSV - [x] Confirm no sensitive information (API keys, secrets) is included in the exported agents #### For configuration changes: - [x] `.env.default` is updated or already compatible with my changes - [x] `docker-compose.yml` is updated or already compatible with my changes - [x] I have included a list of my configuration changes in the PR description (under **Changes**) No configuration changes required - this only adds test data and a loading script.
1676 lines
67 KiB
JSON
1676 lines
67 KiB
JSON
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"description": "Overview:\nFinding a domain name that fits your brand shouldn\u2019t take hours of searching and failed checks. The Domain Name Finder Agent turns your pitch into hundreds of creative, brand-ready domain ideas\u2014filtered by live availability so every result is actionable.\n\nHow It Works\n1. Input your product pitch, company name, or core keywords.\n2. The agent analyzes brand tone, audience, and industry context.\n3. It generates a list of unique, memorable domains that match your criteria.\n4. All names are pre-filtered for real-time availability, so you can register immediately.\n\n\nBusiness Value\nSave hours of guesswork and eliminate dead ends. Accelerate brand launches, startup naming, and campaign creation with ready-to-claim domains.\n\n\nKey Use Cases\n\u2022 Startup Founders: Quickly find brand-ready domains for MVP launches or rebrands.\n\u2022 Marketers: Test name options across campaigns with instant availability data.\n\u2022 Entrepreneurs: Validate ideas faster with instant domain options.",
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"prompt": "You are a domain valuation expert tasked with ranking a list of domain names based on their value and relevance to a specific product. You will be provided with two key pieces of information:\n\n1. A product pitch:\n<product_pitch>\n{{product_pitch | safe}}\n</product_pitch>\n\n2. A list of domain names to rank:\n<domain_list>\n{{domains | safe}}\n</domain_list>\n\nYour task is to analyze these domains and rank them based on two primary factors:\n1. The inherent value of the domain name (most important)\n2. The relevance and potential value of the domain for the specific product described in the product pitch\n\nPlease follow these steps:\n\n1. Read the product pitch carefully and extract key product features and target audience information. List these in <product_analysis> tags.\n\n2. Identify relevant keywords for the product based on the pitch. List these in <keywords> tags.\n\n3. For each domain in the provided list - carefully consider it, then pick your top 10 domains from the list for the following analysis:\n a. Evaluate the domain based on the following factors:\n - Length (number of characters)\n - Memorability\n - Brandability\n - Keyword relevance\n - TLD (Top-Level Domain)\n - Potential commercial value\n\n b. Calculate a Domain Quality Score (1-10) using the following method:\n - Length Score (LS):\n 10: 1\u20134 chars\n 9: 5\n 8: 6\n 7: 7\n 6: 8\n 5: 9\n 4: 10\n 3: 11\u201312\n 2: 13\u201314\n 1: 15+\n\n - Word Score (WS):\n * Base (BWC): 1 word =5, 2 words =4, 3w=3, 4w=2, 5+ words =1\n * Quality Modifier (WQM): +1 English dictionary word, 0 common/brandable, \u20131 meh brand/obscure foreign, \u20132 unpronounceable\n * Word Score (WS) = clamp(BWC + WQM, 1\u20135)\u00d72\n\n - Penalties: \u20131 hyphen, \u20131 number, \u20130.5 triple letter\n\n - Final Score = clamp(round(0.6\u00d7WS + 0.4\u00d7LS + penalties), 1\u201310)\n\n c. Consider how the domain relates to the product described in the product pitch.\n\nWrap your analysis in a single set of <domain_analysis> tags. \nInclude the following for each domain:\n1. Verify that the domain is present in the original list provided.\n2. A table with the following columns: Factor, Calculated Score, Justification.\n3. The calculated Domain Quality Score, showing each step of the calculation.\n4. An explanation of how the domain relates to the product pitch.\n\nAfter evaluating your potential top 10 domains, present your final ranking as a newline-separated list of domains inside a single complete set of <domains> XML tags. Ensure that only domains from the original list are included in your ranking.\n\nIf there are more than 30 domains in the list, just list your top 30.\n\nExample output format:\n\n<domains>\ndomain1.com\ndomain2.net\ndomain3.org\n</domains>\n\nPlease proceed with your evaluation and ranking of the provided domain list.",
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