Explain what the .faf format is — the IANA-registered, portable context file (application/vnd.faf+yaml) that gives any AI instant project understanding. Returns a plain-language overview of the format and its purpose. Use this when you or the user are new to FAF and want the concept before running other tools.

Calculate a project.faf AI-readiness score (0-100%) from the populated context slots. Returns the percentage and tier, and with details a slot-by-slot breakdown with improvement suggestions. Use this to measure how complete the AI context is and what to fill next.

Create a project.faf for a project, making it instantly AI-readable. Returns the new file location and starting score. Accepts a path or bare project name (e.g. ~/Projects/my-app, my-app) and omitting it uses the current directory.

Validate a project.faf for structural integrity and field consistency. Returns trust metrics flagging malformed, missing, or contradictory data. Use this to confirm the context is sound before relying on it or syncing it to other formats.

Sync a project.faf with CLAUDE.md so the two stay aligned. Returns what was written. Use this for the single CLAUDE.md target; use faf_bi_sync to fan out to AGENTS.md, .cursorrules, and GEMINI.md as well.

Bi-directionally sync a project.faf with CLAUDE.md and, with the format flags or all, also AGENTS.md, .cursorrules, and GEMINI.md. Returns the formats written and any conflicts. Use this to keep every AI tool context file aligned from the single .faf source.

Inspect the human_context fields and rate each empty/generic/good/excellent. Returns the ratings; with protect it locks good/excellent fields from being overwritten, with unlock it releases them. Use this to gauge context quality and guard your best answers.

Set or show the active project path that later faf_ calls resolve against. Returns the current context path. Call this once at the start of a session so the other tools target the right project.

Drive a project.faf to 100% through a guided interview — returns the next questions for the missing human-context and goal fields, then applies the answers passed back. Returns the updated score after each round. Use this to close the gap to a complete context when auto-detection cannot fill the human slots.

Run the full setup pipeline in one call — init, stack detection, sync, bi-sync, and score — taking a project from no context to a complete project.faf. Returns the final AI-readiness score and what was created. Use this as the fast path on a fresh project; use the individual tools when you need finer control.

Diagnose a project.faf setup — report missing files, empty or weak slots, and common configuration issues, each with how to fix it. Returns a prioritized checklist. Use this when your score is low and you need to know why.

Import, export, or sync context between AGENTS.md (the OpenAI/Codex convention) and project.faf. Returns the merged or written result for the chosen action. Use this to keep a Codex/OpenAI-style AGENTS.md and your .faf in agreement from one source.

Import, export, or sync context between .cursorrules (the Cursor IDE convention) and project.faf. Returns the merged or written result for the chosen action. Use this to keep Cursor rules and your .faf in agreement from one source.

Import, export, or sync context between GEMINI.md (the Google Gemini CLI convention) and project.faf. Returns the merged or written result for the chosen action. Use this to keep a Gemini context file and your .faf in agreement from one source.

Generate a project.faf from any public GitHub repository URL — fetches the repo and extracts its stack and context. Returns the generated .faf. Use this to bootstrap context for a project you have the URL for but not cloned locally.