project/
├── package.json     ← npm reads this
├── project.faf      ← AI reads this
├── README.md        ← humans read this
└── src/

Every building requires a foundation. FAF is AI's foundational layer.

You have a package.json. AI needs you to add a project.faf. Done.

Git-Native. project.faf versions with your code — every clone, every fork, every checkout gets full AI context.
No setup, no drift, no re-explaining.

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Install

bunx faf auto                 # Bun — zero install, fastest path
npx faf auto                  # npm — works everywhere
pnpm dlx faf auto             # pnpm — zero install
brew install wolfe-jam/faf/faf-cli && faf auto   # Homebrew (auto-taps)

faf with no arguments shows your project's score. faf auto fills what it detects in the repo, and suggests the goal and six W's for you to confirm in faf go.

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Quick Start

# ANY GitHub repo — one shallow clone, no install, 2 seconds
bunx faf-cli git https://github.com/facebook/react

# Your own project
bunx faf-cli init              # Create .faf
bunx faf-cli auto              # Fill the tech slots from the repo, then score
bunx faf-cli go                # Confirm the goal and six W's, suggested in gray

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Nelly Never Forgets

Run faf with no arguments:

faf-cli dogfoods itself — project.faf is source DNA; CLAUDE.md, GEMINI.md and AGENTS.md are authored from it via faf export; AGENTS.md keeps a hand-written section below faf's block.

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Commands

Command	What it does
faf init	Create project.faf from your local project; suggest the goal and six W's
faf git <url>	Instant .faf from any GitHub repo (a shallow clone)
faf auto	Detect the stack, fill the slots it detects, score; suggest the goal and six W's
faf go	Fill the human slots: each suggestion in gray, Tab to edit, Enter to confirm
faf score	Check AI-readiness (0–100%)
faf export	Author AGENTS.md, CLAUDE.md, GEMINI.md, .cursorrules
faf sync	.faf → CLAUDE.md, one way (faf's block only)
faf memory	.fafm soul ops — convert Claude memory, etch, recall, ls, show
faf diff / log	Semantic context diff + score timeline across git history
faf hooks --install	Pre-commit guard against context regression
faf taf setup	Write the CI workflow that prints a Test Receipt for every run (JavaScript with Jest, Vitest or Bun; Python; Go; Rust; Java with Maven or Gradle; .NET)
faf taf receipts	Your Test Receipts in the terminal, newest first
faf compile / decompile	.faf → .fafb v2 sealed brick; decompile shows sections as JSON
faf check	Validate a .faf file
faf show	Render project.faf to a browsable HTML page
faf formats	List supported stacks and formats

Run faf --help for the full command set and options.

Memory (.fafm)

Portable agent memory in the IANA-registered .fafm format. Same INTEROP as claude-fafm-sdk 1.0.

# Claude Code memory dir → soul.fafm
faf memory convert ~/.claude/projects/.../memory -o soul.fafm

faf memory ls                    # ranked facts
faf memory recall "your query"   # deterministic filter + rank
faf memory etch "a durable fact" --id my-fact
faf memory show

What's New in v8.10.0 — The Human Slots Edition

AI suggests, you confirm. faf no longer writes your project's goal or six W's: it suggests them, and you confirm each one in faf go.

• Suggestions in gray. faf go shows each suggestion with where it came from (README.md § Why, package.json description). Tab to edit, Enter to confirm, type to replace, skip to leave it empty. faf init, faf auto and faf git say how many are waiting.
• Only facts are suggested. Markup, link and label rows, greetings, install lines and fragments are rejected; a notice or callout (deprecated, sponsored by, Warning:…) is never the goal; a long first paragraph gives its first sentence, whole. The README leads the goal.
• faf-facts. The six W's ask for one line where every word earns its place. how is how it works; when is the stage it is at, and since when.
• Breaking for library users: assembleFreshFaf, updateExistingFaf and authorFafFromRepo return the goal and six W's empty. Files you already have are not changed.
• faf go input. Backspace removes a whole character (emoji, CJK), other questions use readline again, and piped answers are read in order.

Earlier editions: CHANGELOG.md · Releases

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Custom instructions

Your own rules for the AI — "use full words in identifiers," "use bun, not npm" — go in project.faf under ai_instructions.warnings. They land at the top of every AGENTS.md faf writes, verbatim and non-destructive.

→ How to add custom rules · docs.faf.one

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Scoring

✪ Trophy 100% — all or nothing. From v6.6.0 onward, faf-cli recommends only Trophy. 100% on the FCL is what makes the layers above (MD instructions, Agents, AI tooling) work — sub-Trophy leaves gaps that AI guesses on. Sub-Trophy tiers (including Bronze 85) remain on the ladder as honest interim states — they are not deleted; we just no longer aim for 85 as the goal.

Tier	Score	Status
✪ Trophy	100%	AI never has to guess — target
★ Gold	99%+	1 slot from Trophy
◆ Silver	95%+	Close — keep going
◇ Bronze	85%+	On the ladder (was the old recommend-min; not the target)
● Green	70%+	Interim — keep going
● Yellow	55%+	AI flipping coins
○ Red	<55%	AI working blind
♡ White	0%	No context at all

Always-33. The score is filled ÷ active across all 33 Mk4 slots. Your app-type decides which slots are active; the rest are slotignored and stay visible. Same file, same engine, same number — see docs/SCORING.md.

One score, three glyphs: ✪ work (CLI · docs · receipts) · 🏆 social (X · blogs) · Trophy Mark PNG (brand). Source of truth: src/core/tiers.ts.

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Sync

sync:      .faf  ───→  CLAUDE.md   (one way: faf's block only)
tri-sync:  .faf  ───→  CLAUDE.md + Claude Code's MEMORY.md   (Pro: faf's block only; Claude's notes kept)

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Docs

The full manual lives at docs.faf.one — facts for devs, faf-cli first. One-page overview: faf-cli.vercel.app.

• Getting started — install · run · use
• Cards — one .fafa → A2A · Server Card · registry · AI Catalog · ARD
• Custom rules — pin instructions your AI must follow

For a specific agent: Grok, xAI & Cursor 👀 · Claude Code 👀 · Bun 👀

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Recent editions

Pivotal releases — full history in CHANGELOG.md:

• v8.10 — Human Slots — AI suggests the goal and six W's; you confirm each one in faf go.
• v8.9 — Write-Once — a birth certificate that can't be reissued, checked against its birth commit.
• v8.0 — Always33 — one engine, one number: the same score everywhere.
• v7.1 — AGENTS.md — faf export --agents authors a complete, non-destructive AGENTS.md.
• v7.0 — GIT — context goes git-native: faf diff / log / hooks.
• v6.16 — Know Your Stack — every emitted file labels your stack identically.
• v6.15 — Copilot — faf export --copilot writes the file GitHub Copilot reads.
• v6.14 — Loop — faf loop drives any repo to ✪ 100% or the honest human wall.
• v6.7 — HTML — faf show renders a .faf to a browsable page. (FAF defines. AGENTS.md instructs. AI codes. HTML shows.)
• v6.6 — Trophy — 100% or nothing.
• v6.0 — Bun — ground-up rewrite; single portable binary, four platforms.

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Compiled Binaries

Bun's single-file compiler produces standalone binaries — no runtime needed.

bun run compile                # Current platform
bun run compile:all            # darwin-arm64, darwin-x64, linux-x64, windows-x64

Ship faf as a single binary for CI/CD, Docker, or air-gapped environments.

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Architecture

src/
├── cli.ts              ← Entry point (Commander registrations)
├── commands/           ← one file per faf subcommand
├── core/               ← Types, slots (Mk4), tiers, scorer, schema
├── detect/             ← Framework detection, stack scanner
├── interop/            ← YAML I/O, CLAUDE.md, AGENTS.md, GEMINI.md
├── ui/                 ← Colors (#00D4D4), display
└── wasm/               ← faf-scoring-kernel wrapper (Rust → WASM)

Toolchain: Bun (test, build, compile) · TypeScript (strict) · WASM (scoring kernel)

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Testing

Robust. Reliable. Next-level WJTTC tested. — The Foundation Edition.

npm test                       # extensive WJTTC + e2e suite

• WJTTC Build Resilience — regression classes locked.
• WJTTC Kernel Stress — WASM kernel boundary tests.
• e2e lifecycle — commands in sequence.

Test reports in reports/.

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Support

• GitHub Discussions — Questions, ideas, community
• Email: [email protected]

If faf-cli has been useful, consider starring the repo — it helps others find it.

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Citation

If you use faf-cli or the .faf / .fafm / .fafa formats in research or production, please cite the format papers:

Wolfe, J. (2025). Format-Driven AI Context Architecture: The .faf Standard for Persistent Project Understanding. Zenodo. https://doi.org/10.5281/zenodo.18251362

Wolfe, J. (2026). Permanent Memory and Instant Recall: The .fafm Standard for Multi-Profile AI Agent Memory. Zenodo. https://doi.org/10.5281/zenodo.20348942

Wolfe, J. (2026). Why Agents Need a Passport: .fafa — Portable Identity for the Agentic Era. Zenodo. https://doi.org/10.5281/zenodo.21951641

BibTeX

@article{wolfe2025faf,
  title     = {Format-Driven AI Context Architecture: The .faf Standard for Persistent Project Understanding},
  author    = {Wolfe, James},
  year      = {2025},
  month     = {nov},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.18251362},
  url       = {https://doi.org/10.5281/zenodo.18251362}
}

@article{wolfe2026fafm,
  title     = {Permanent Memory and Instant Recall: The .fafm Standard for Multi-Profile AI Agent Memory},
  author    = {Wolfe, James},
  year      = {2026},
  month     = {may},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.20348942},
  url       = {https://doi.org/10.5281/zenodo.20348942}
}

@article{wolfe2026fafa,
  title     = {Why Agents Need a Passport: .fafa — Portable Identity for the Agentic Era},
  author    = {Wolfe, James},
  year      = {2026},
  month     = {aug},
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.21951641},
  url       = {https://doi.org/10.5281/zenodo.21951641}
}

License

MIT — Free and open source

IANA-registered: application/vnd.faf+yaml (Context Layer) · application/vnd.fafm+yaml (Memory Layer) · application/vnd.fafa+yaml (Agent Layer)

format | driven 🏎️⚡️ wolfejam.dev · faf.one/cli