Extract AI context from any coding site
FAF - AI Context ⚡️ Fast AF Analyze web-based development environments for AI-readiness. Professional scoring and reporting for GitHub and modern development platforms. ⚡ ONE-CLICK ANALYSIS Get instant AI-readiness scores (0-100%) for any development environment. Download comprehensive analysis reports as .txt files for easy viewing and sharing. 🎯 KEY FEATURES - Web-based development platform analysis - AI-readiness scoring with detailed breakdowns - Professional downloadable reports (.txt format - gateway to full .faf capabilities) - Development-focused scope (no generic website rating) - 100% private - no data collection - Zero network requests 🤖 UNIVERSAL COMPATIBILITY Generated reports work seamlessly with any AI assistant or coding tool that accepts context files. The .txt download introduces you to the FAF format - upgrade to full .faf integration via MCP for advanced features. 🔒 PRIVACY FIRST Everything runs locally. Your code never leaves your machine. No tracking, no accounts required. 📊 PERFECT FOR - Evaluating repositories before AI assistance - Code reviews with AI tools - Learning new development environments - Validating project AI-readiness The FAF format is becoming the universal standard for AI context - like package.json for dependencies. Free forever for individual developers. Advanced .faf features available through MCP integration. Learn more: https://faf.one Version 1.0.3
Details
Version
1.0.3
Updated
September 16, 2025
Size
284KiB
Languages
Developer
Non-trader
This developer has not identified itself as a trader. For consumers in the European Union, please note that consumer rights do not apply to contracts between you and this developer.
Privacy
.faf - AI-Context⚡️Fast AF has disclosed the following information regarding the collection and usage of your data. More detailed information can be found in the developer's privacy policy.
.faf - AI-Context⚡️Fast AF handles the following:
Web history
Website content
This developer declares that your data is
- Not being sold to third parties, outside of the approved use cases
- Not being used or transferred for purposes that are unrelated to the item's core functionality
- Not being used or transferred to determine creditworthiness or for lending purposes
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