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 grimoire-rs/grimoire --skill meta-maintain-configgit clone --depth 1 https://github.com/grimoire-rs/grimoireWrote 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/grimoire-rs/grimoire/meta-maintain-config)<a href="https://agentmods.dev/skills/grimoire-rs/grimoire/meta-maintain-config"><img src="https://agentmods.dev/badge/skills/grimoire-rs/grimoire/meta-maintain-config/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/grimoire-rs/grimoire/meta-maintain-config"><img src="https://agentmods.dev/badge/skills/grimoire-rs/grimoire/meta-maintain-config.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00069 | $0.01804 |
| Opus 5.5 | $0.00028 | $0.00722 |
| Sonnet 5.5 | $0.00014 | $0.00361 |
| Haiku 4.5 | $0.00007 | $0.00180 |
Grade A, and why
meta-maintain-config 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 28d 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.
How it starts
The opening of the file, as written. The whole thing — 159 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Configuration Maintenance
Keep .claude/ directory living knowledge base. Stay current with project + AI tooling best practices.
Read .claude/rules/meta-ai-config.md first — defines conventions, budget constraints, anti-patterns this skill enforces.
Modes
create — New Artifact
-
Discover + Research — Invoke canonical multi-agent research primitive from
/hex-plan(Phases 1-2). Spawn workers parallel:- an explorer pass (1-2): existing
.claude/patterns, conventions, cross-references, neighbors of artifact - researcher pass (1-3, split by axis): Claude Code docs (
code.claude.com/docs), domain best practices, community patterns for artifact topic
Persist substantial findings as
.agents/research/research_[topic].mdfor reuse. See/hex-plan"Research as a Reusable Primitive". - an explorer pass (1-2): existing
-
Draft — Follow
meta-ai-config.mdconventions:- Respect context budget (<200 lines rules, <500 lines skills)
- Use
paths:scoping for rules unless truly global - Skills: write description as "what + when to use" (max 1024 chars)
- Use progressive disclosure — SKILL.md overview, reference files for detail
- Add
disable-model-invocation: truefor action skills with side effects
-
Integrate — Update AGENTS.md tables, meta-rule inventory
-
Validate — Run audit checks (see below)
audit — Check All Artifacts
Context budget audit:
- AGENTS.md under 280 lines?
- Each global rule under 200 lines?
- Count global rules — too many degrades performance
- Skill descriptions total within 2% context budget?
Structural audit:
- Every SKILL.md has
name+description? - No
allowed-toolsin skill frontmatter? - All persona skills have
user-invocable: true? - Hook scripts executable?
Dead glob audit:
- For each scoped rule, do
paths:patterns match existing files? - After directory renames, glob patterns silently fail — verify with:
find . -path "pattern" | head -1
Cross-reference audit:
- Rules referencing other rules → targets exist?
- Skills referencing rules → correct filenames?
- Agents referencing rules → still valid?
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.
- 28d ago Changed · +69 tokens per session 77795eb75b3d
- 1mo ago First seen · 159 lines · 0 tokens per session scan A df977cbb0dca
meta-maintain-config is a skill published in the GitHub repository grimoire-rs/grimoire (14 stars, last pushed today), licensed Apache-2.0. It adds 69 tokens to every session and 1,804 once invoked, about $0.0003 per session on Opus 5.5. 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
vuln-scanner
Audit trending repos for real security vulnerabilities and disclose responsibly - scan and route findings (PVR / dependency PR), re-submit queued advisories, and send armed email disclosures.
fork-fleet
Fork divergence monitor - tracks where the fleet's active forks diverge in CODE (unique commits, new/modified skills) and CONFIG (enable/var/model/schedule vs upstream), gated on real change.
pack-submit
Package one of this agent's own skills as a standalone community pack and submit it to the aeon registry as a PR.
shiplog
Recap of everything shipped since the last run - cross-repo PRs, security fixes, star deltas, and X traction, synthesized into a digest article and a ready-to-post shiplog in your voice.
token-pick
One token recommendation and one prediction market pick - scored, quantified, with a skip branch when signals are weak.
autoresearch
Evolve a skill by generating variations, evaluating them, and updating the best version.