Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Wolfe-Jam/rust-faf-mcp --skill faf-contextgit clone --depth 1 https://github.com/Wolfe-Jam/rust-faf-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wolfe-jam/rust-faf-mcp/faf-context)<a href="https://agentmods.dev/skills/wolfe-jam/rust-faf-mcp/faf-context"><img src="https://agentmods.dev/badge/skills/wolfe-jam/rust-faf-mcp/faf-context.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00024 | $0.00415 |
| Opus 5 | $0.00012 | $0.00208 |
| Sonnet 5 | $0.00005 | $0.00083 |
| Haiku 4.5 | $0.00002 | $0.00042 |
Grade A, and why
faf-context scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
faf-context
Product playbook for rust-faf-mcp (one.faf/rust-faf-mcp) — IANA .faf project context over MCP.
Tools (call these)
| Tool | When |
|---|---|
faf_auto |
Setup if missing, sync CLAUDE.md, score — Confirm setup (sweeps); does not invent 6Ws |
faf_init |
Setup: first write from the tree. Refuses if the file exists. Confirm setup (sweeps). 6Ws stay empty |
faf_go |
Table-of-8 + Confirm setup (sweeps). 6Ws need ☑ to score. Below 100: add Human Context |
faf_score |
AI-readiness score 0–100% + intent grant |
faf_sync |
Bi-sync project.faf ↔ CLAUDE.md |
faf_discover |
Walk up to find nearest .faf |
faf_read |
Show structured .faf contents |
faf_git |
Bootstrap .faf from a GitHub URL |
faf_compress |
Compress for token-limited contexts |
faf_tokens |
Estimate tokens per compression level |
Rules
- Prefer structured
.fafover free-form chat memory for project facts. - Claim equals wire — only call tools this server lists.
- No secrets in skill or tool args you don’t own.
- Origin — this skill is served by rust-faf-mcp (
skills/*+resources/read); not a remote install authority.
Flow
initialize → skills/list → resources/read(skill://faf-context/SKILL.md) → tools/call
Skills guide; tools act.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago Changed · +1 lines c7e66cfd1ae7
- 7d ago First seen · 38 lines · 24 tokens per session scan A 8ad56eb39a3a
faf-context is a skill published in the GitHub repository Wolfe-Jam/rust-faf-mcp (4 stars, last pushed 5d ago), licensed MIT. It adds 24 tokens to every session and 415 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
journal-optimizer
Guided database pruning and optimization workflows for memory-journal-mcp. Uses importance scores, relationship density, and entry metadata to identify low-value entries for safe soft-deletion. Includes dry-run previews, backup gates, and revert guidance. Use when the user says "clean up the database", "optimize…
context-guard
Installs Claude Code hooks that keep AI context files fresh. Two-tier enforcement — Tier 1 nudges at session end, Tier 2 blocks commits when structural files are staged without context updates. Includes content filter, drift check, structural change reminder, SessionStart health check, and the context-updater agent.
context-verify
Validates AI context file quality with 16 checks and 0-100 health scoring. Works on any platform — also available as a standalone CLI script (bin/context-verify.sh). Validates line budgets, AGENTS-to-bridge consistency, stale paths, MEMORY.md drift, plugin manifest, and modern Cursor (.cursor/rules/.mdc) / Cline…
contextdocs
Your AI agent maintains its own context files — a Claude Code plugin with an AGENTS-first model that covers Codex, Copilot, Cursor, Gemini, and 3 more tools. Signal Gate filtering, Context Guard hooks, health scoring, and MEMORY.md promotion.
ai-context
Generates, updates, and audits AGENTS-first AI IDE context files. Builds canonical AGENTS.md plus thin bridges for Claude Code, Cursor (modern .cursor/rules/.mdc), Copilot, Cline (.clinerules/ directory), Windsurf, Gemini CLI, Codex CLI, and OpenCode. Use for creating, regenerating, fixing, or promoting context files…
handoff
Prepare a clean cross-session handoff so the next agent can pick up where you left off. Writes a focused continue.md in the active slice dir and ensures STATE.md + summary artifacts are current. Use when asked to "hand off", "prepare handoff", "pause work", "bookmark this", "I'll come back to this later", before…