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faf-cli

v3.4.4

Published

Anthropic-Approved codebase that powers claude-faf-mcp • Persistent project context, on-demand • Format-driven CLI • Open Source Universal Standard • MIT License

Readme

Universal CLI for FAF (Foundational AI-context Format) - Terminal-based tooling for creating, scoring, and improving project.faf files that provide persistent AI context

NPM Downloads Homebrew Website License: MIT


What's New in v3.4.4

Boris-Flow - 12/12 integration tests for publish readiness. Championship-grade validation.

./tests/boris-flow.test.sh
# Validates: version, init, auto, score, Claude Code detection, non-TTY safety

faf demo sync - Live bi-sync demonstration. Show your team how .faf <-> CLAUDE.md sync works.

faf demo sync           # Run the demo
faf demo sync --fast    # Speed run

TL;DR

Problem: AI needs persistent project context to work at its best.

Solution: The .faf format provides that context. This CLI creates, scores, and improves .faf files from your codebase in the IANA-registered format.

How it works: Run faf init to create your .faf file. Get a score (0-100%) showing context quality. Higher scores = AI more in-tune with your project. Use faf auto and other commands to improve your score quickly.

Install:

# npm (works everywhere)
npm install -g faf-cli

# Homebrew (macOS/Linux)
brew install faf-cli

Quick start:

cd your-project
faf init        # Creates project.faf file
faf score       # Check AI-readiness (0-100%)

CLI vs MCP clarity:

  • faf-cli (this): Terminal-based tool for scripts, automation, and local development
  • claude-faf-mcp (npm): MCP server for Claude Desktop via protocol integration

Same .faf format, different execution layers. Same Project DNA and scoring. Same capabilities (create, score, improve). Choose based on your workflow.

Website | GitHub | Discussions


Project DNA Positioning

At 55% you are building your project with half a blueprint and basically flipping a coin with AI. .FAF defines, and AI becomes optimized for Context with the project.faf file.


Quick Start

Installation

# npm (works everywhere)
npm install -g faf-cli

# Homebrew (macOS/Linux)
brew install faf-cli

Generate Your First .faf File

# Initialize with IANA-registered format
faf init

# Output: project.faf with official media type
# Content-Type: application/vnd.faf+yaml

What just happened:

  • Created project.faf file (IANA-registered format)
  • Generated project DNA (architecture, dependencies, quality score)
  • Ready for any AI (Claude Code, Gemini, Cursor, Codex, Warp, etc.)
  • Official Internet standard format

More Commands

# Auto-detect and enhance
faf auto

# Check your AI readiness
faf score

# Discover your stack's formats
faf formats

# Sync with CLAUDE.md
faf bi-sync

That's it! Your AI now has perfect context.


Human Context (The 6 Ws)

Boost your score by 25-35% with human context - the information only YOU know about your project.

Auto-Extract from README

# Preview what can be extracted
faf readme

# Apply extracted content to empty slots
faf readme --apply

# Overwrite all slots (even filled ones)
faf readme --apply --force

Manual Entry

# Non-interactive (works in Claude Code)
faf human-set who "Frontend team at Acme Corp"
faf human-set what "Customer dashboard with real-time analytics"
faf human-set why "10x faster than previous solution"

# Interactive mode (terminal only)
faf human

Quality Check & Protection

# Inspect quality of human_context fields
faf check

# Output shows quality levels:
#   empty     - Not filled
#   generic   - Placeholder or too short
#   good      - Quality content
#   excellent - High-value content

# Lock good content from being overwritten
faf check --protect

# Remove all protections
faf check --unlock

Protected fields are skipped by faf readme and faf auto, preventing accidental overwrites of quality content.


Core Features

44 Championship Commands

  • faf auto - Zero to Podium in one command
  • faf init - Create project.faf from your project
  • faf readme - Smart 6 Ws extraction from README.md
  • faf human - Interactive human context entry
  • faf human-set - Non-interactive field setting (Claude Code compatible)
  • faf check - Quality inspection + field protection
  • faf enhance - Real AI analysis and improvements
  • faf score - AI-readiness scoring (0-100%)
  • faf formats - 153 formats across 17-level pyramid
  • faf bi-sync - Bidirectional .faf ↔ CLAUDE.md (8ms!)
  • faf dna - Evolution journey tracking

Run faf --help for complete command reference

IANA-Registered Standard

  • Official MIME type: application/vnd.faf+yaml
  • Recognized at Internet scale (same as PDF, JSON, XML)
  • Proper HTTP Content-Type headers
  • Browser and email client support
  • Universal format for AI context

Championship Performance

  • <50ms all commands target
  • 18ms average execution
  • 8ms bi-sync achieved
  • 0ms operations possible (unmeasurable speed!)
  • F1-grade engineering

Universal AI Support

Works with Claude Code, OpenAI Codex CLI, Gemini CLI, Cursor, Warp, Copilot, Windsurf, and all AI coding assistants.

PLUS: AI-Automation platforms (n8n, OpenAI Builder, Google Opal, Make.com)


Project Types (94 Supported)

FAF now understands your project type and scores accordingly. CLI projects don't need frontend slots. Fullstack projects need everything.

How It Works

Set your project type in .faf:

project:
  type: cli          # 9 slots (project + human)
  type: frontend     # 16 slots (+ frontend + universal)
  type: backend-api  # 17 slots (+ backend + universal)
  type: fullstack    # 21 slots (all categories)

Supported Types

9-Slot Types (Project + Human): cli library npm-package pip-package crate gem chrome-extension firefox-extension safari-extension terraform kubernetes docker ansible github-action embedded arduino wasm jupyter smart-contract e2e-tests

13-Slot Types (+ Frontend): mobile react-native flutter ios android desktop electron tauri game unity dapp

14-Slot Types (+ Backend): mcp-server data-science ml-model data-pipeline n8n-workflow python-app

16-Slot Types (+ Frontend + Universal): frontend svelte react vue angular astro

17-Slot Types (+ Backend + Universal): backend-api node-api python-api go-api rust-api graphql microservice strapi

21-Slot Types (All Categories): fullstack nextjs remix t3 mern mean django rails laravel wordpress monorepo turborepo nx lerna pnpm-workspace yarn-workspace

Type Aliases (38 shortcuts)

Use intuitive names - FAF maps them automatically:

| Alias | Maps To | Alias | Maps To | |-------|---------|-------|---------| | api | backend-api | k8s | kubernetes | | cli-tool | cli | rn | react-native | | flask | python-api | expo | react-native | | fastapi | python-api | turbo | turborepo | | express | node-api | next | nextjs | | tf | terraform | gha | github-action |

slot_ignore Escape Hatch

Override type defaults for your specific project:

project:
  type: cli
slot_ignore: [stack.hosting, stack.cicd]  # These won't count

Formats: array [a, b], string "a, b", or shorthand hostingstack.hosting


Documentation


Why FAF CLI?

"README for the AI era" — Gemini CLI

Persistent Context - Your project's DNA lives in project.faf, readable by any AI or human

Universal Format - IANA-registered standard works across Claude, Gemini, Codex, any LLM

Terminal-Native - Built for scripts, automation, and developer workflows

Championship Engineering - F1-inspired performance with strict TypeScript, zero runtime errors


Ecosystem


Development

# Clone
git clone https://github.com/Wolfe-Jam/faf-cli.git
cd faf-cli

# Install & Build
npm install
npm run build

# Test
npm test

# Link locally
npm link

License

MIT License - Free and open source


Built with F1-inspired engineering principles

"It's so logical if it didn't exist, AI would have built it itself" — Claude