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's required fields (faf_version, project.name) and about.* block with faf-cli's validator, and report its real score.

Reconcile project.faf with what the repo manifests say now (package.json name, description, framework dependencies). Dry-run by default: reports the fields that would change. Pass apply:true to write them into project.faf. Does not touch CLAUDE.md — use faf_claude for CLAUDE.md, AGENTS.md, .cursorrules and GEMINI.md.

Write CLAUDE.md from project.faf (one direction: .faf → CLAUDE.md) and, with the format flags or all, also AGENTS.md, .cursorrules and GEMINI.md. Content outside the faf-managed block is preserved. Returns the files written. Use this to keep every AI tool's context file current from one source. (Named faf_bi_sync before 3.0.1; that name still works.)

Inspect the human_context fields and rate each empty/generic/good. Returns the ratings; with protect it records the good fields in _protected_fields as an advisory list (other tools do not enforce it), with unlock it clears that list. Use this to gauge context quality.

Set or show the active project path that later faf_ project tools resolve against (faf_read and faf_write resolve relative paths against the server's working directory instead). Returns the current context path. Call this once at the start of a session so the project 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 setup pipeline in one call — init or merge, stack detection, CLAUDE.md, and score — taking a project from no context to a scored project.faf plus CLAUDE.md; faf_go closes the human slots. 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, the real score with populated/active slot counts, and common configuration issues, each with a fix. Returns a checklist. Use this when your score is low and you need to know why.

Import AGENTS.md (the OpenAI/Codex convention) into project.faf, or write it from 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 .cursorrules (the Cursor IDE convention) into project.faf, or write it from 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 GEMINI.md (the Google Gemini CLI convention) into project.faf, or write it from 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.

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