Foundational AI-context Format Universal, shareable AI-Context for any AI, human or team, regardless of size, location, languages, stack, setup or documentation.

Transform any file into perfect AI context

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.faf is an open format for AI context. Transform individual files or entire projects into structured data that AI instantly understands. Your tech stack, dependencies, architecture, and goals - all in one concise, shareable format.

Instead of explaining your project every time, AI reads your .faf once and knows exactly how to help.

AI tools need context. Files have context. But there's no standard way to measure or structure that context for optimal AI understanding.

# example.faf
version: 1.0
score: 85
type: package
confidence: 0.92
content:
  name: "my-project"
  dependencies: ["react", "typescript", "vite"]
  scripts: ["dev", "build", "test"]
metadata:
  source: "package.json"
  processed: "2024-01-26T12:00:00Z"
  engine: "faf-v1"

1. Universal - 150+ file types supported
2. Scored - 0-100% context completeness score
3. AI-Optimized - Structured for maximum AI comprehension
4. Human-Readable - Simple, structured format
5. Shareable - One file contains complete context

Input: package.json

{
  "name": "my-app",
  "version": "1.0.0",
  "dependencies": {
    "react": "^18.0.0"
  }
}

Output: package.faf (85% context score)

version: 1.0
score: 85
type: package
content:
  name: "my-app"
  version: "1.0.0"
  dependencies: ["react@^18.0.0"]
metadata:
  processed: "2024-01-26"

• 🎯 Measure - Know exactly how complete your AI context is
• 📊 Optimize - See what's missing, improve your score
• 🚀 Standardize - One format for all file types
• 🤖 AI-Ready - Optimized for LLM consumption

• File Conversion: Transform any file type into .faf format

• Project Context: Create a single .faf file for your entire project

• Build Integration: Companies can create custom implementations

• AI Optimization: Perfect context for any AI tool

  🚀 Get Started Now

  For Developers - Install the CLI

  # Install via npm (works everywhere)
  npm install -g faf-cli
  
  # Or via Homebrew (macOS/Linux)
  brew install faf-cli
  
  # Then initialize your project
  cd your-project
  faf init
  
  One command. Zero config. Championship context. 🏁
  
  For Claude Desktop Users - Install MCP Server
  
  npm install -g claude-faf-mcp
  
  Then add to your Claude Desktop config. https://github.com/Wolfe-Jam/claude-faf-mcp
  
  Try Online - No Install Required
  
  🌐 https://fafdev.tools/ - Web implementation (Beta)
  
  Drop your files, get instant .faf context!
  
  ---
  📚 Learn More
  
  - ./SPECIFICATION.md - Complete .faf format specification
  - ./example.faf - See a real .faf file
  - ./WHERE-TO-FIND-FAF.md - All FAF ecosystem tools
  - https://github.com/Wolfe-Jam/faf-cli - 41 championship commands
  - https://github.com/Wolfe-Jam/claude-faf-mcp - Claude Desktop integration
  
  ---
  🎯 Quick Start Paths
  
  Path 1: Fast Setup (5 minutes)
  npm install -g faf-cli && cd your-project && faf init
  
  Path 2: Try Before Installing
  Visit https://fafdev.tools/ and drop a file to see .faf in action
  
  Path 3: Claude Desktop Integration
  Install https://github.com/Wolfe-Jam/claude-faf-mcp for seamless AI context
  
  ---
  Need help? Check our https://github.com/Wolfe-Jam/faf-cli/discussions or join the community!
  

🏁 Early Stage - Specification v1.0 released January 2025 🏁 Stable & Growing - Specification v1.1.0

Latest Release: v1.1.0 (October 2025)

• Professional-grade documentation
• 5 real-world examples (n8n, OpenAI, CLI, TypeScript, Chrome Extension)
• Enhanced tooling integration
• Semantic versioning established

Format Stability:

• ✅ Core format is stable and production-ready
• ✅ 10,000+ .faf files generated across ecosystem
• ✅ Universal AI support (Claude Code, OpenAI Codex CLI, Gemini CLI, Cursor, Warp)
• ✅ Backwards compatible (v1.0 files remain valid)

Ecosystem Tools:

• faf-cli - 41 championship commands, 153+ format support
• claude-faf-mcp - Claude Desktop integration
• fafdev.tools - Web-based .faf generator (Beta)

Specification History:

• v1.1.0 (October 2025) - Professional upgrade, real-world examples
• v1.0 (January 2025) - Initial public release

This is an open standard. Ideas, feedback, and contributions welcome.

MIT - Use freely, build anything.

Created by wolfejam.dev

**STOP .fafFing About! Let's RACE 🏎️⚡️🏁