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 agentmods add skills/minhthang1009/dotclaude/audit-pluginnpx skills add MinhThang1009/dotclaude --skill audit-plugingit clone --depth 1 https://github.com/MinhThang1009/dotclaudeWrote 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/minhthang1009/dotclaude/audit-plugin)<a href="https://agentmods.dev/skills/minhthang1009/dotclaude/audit-plugin"><img src="https://agentmods.dev/badge/skills/minhthang1009/dotclaude/audit-plugin.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 | $0.00121 | $0.03436 |
| Opus 5 | $0.00060 | $0.01718 |
| Sonnet 5 | $0.00024 | $0.00687 |
| Haiku 4.5 | $0.00012 | $0.00344 |
Grade A, and why
audit-plugin 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 5d 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit Plugin Skill
Audit the content quality of a Claude Code plugin through multiple independent review rounds, fix only what the user approves, and loop until convergence. The target is the plugin path passed as the skill argument (<plugin-path>); if no argument was given — or the path does not exist, or it contains no .claude-plugin/plugin.json (not a plugin) — stop and ask the user before proceeding.
Core principles: every claim must carry a verbatim quote + file:line; finders maximize coverage, a validator filters false positives afterward; whoever fixes never signs off on their own fixes; the user approves the scope and every design decision.
Stage 0 — Scope
- List 100% of the plugin's files (plugin.json, README, SKILL.md, references/, examples/, hooks/, commands/, agents/). Print the list so the user sees the audit scope.
- Classify the plugin to decide whether Stage 6 applies:
- Executable workflow (a skill that drives a pipeline, has hooks/scripts) → benchmark applies.
- Content-only (output style, rules, pure reference) → skip Stage 6 and say why.
- Agents/commands-only (ships agents or commands but no pipeline-driving skill) → treat as content-only for Stage 6, unless a command is itself an executable pipeline — then benchmark that command.
- Check the plugin is reachable through EVERY loading mechanism the repo actually uses —
.claude-plugin/marketplace.json,enabledPluginsin settings, sync configs (e.g. a load list consumed by a sync script), junctions/symlinks. Marketplace registration alone proves nothing if the repo loads skills another way; a gap in any one mechanism is a structural finding — record it now and carry it into the Stage 1 findings list (it enters the ledger with everything else). ALWAYS diff the installed-cache copy (~/.claude/plugins/cache/...) against the repo copy of the target plugin — even when the plugin is disabled; a stale cache is a single USER ACTION here instead of a recurring finding in every fresh round. - Tell the user the expected cost BEFORE Stage 1 begins: ~80–95k tokens per fresh-review round (up to 4 rounds), plus the benchmark figures in
references/benchmark-guide.md§4 if Stage 6 may apply. - Apply pending self-updates — read THIS plugin's own
improvement-proposals.md; if criteria-update proposals are marked PROPOSED, ask the user once whether to apply them to the canonical block before this audit begins, then mark each APPLIED or DECLINED (dated). This step is the trigger that closes the self-update loop — without it the loop only ever writes.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 108 lines · 121 tokens per session scan A 965646af56c3
audit-plugin is a skill published in the GitHub repository MinhThang1009/dotclaude (20 stars, last pushed 1mo ago), licensed MIT. It adds 121 tokens to every session and 3,436 once invoked, about $0.0006 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…