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 GoogilyBoogily/googilyboogily-claude-power-tools --skill agent-auditgit clone --depth 1 https://github.com/GoogilyBoogily/googilyboogily-claude-power-toolsWrote 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/googilyboogily/googilyboogily-claude-power-tools/agent-audit)<a href="https://agentmods.dev/skills/googilyboogily/googilyboogily-claude-power-tools/agent-audit"><img src="https://agentmods.dev/badge/skills/googilyboogily/googilyboogily-claude-power-tools/agent-audit/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/googilyboogily/googilyboogily-claude-power-tools/agent-audit"><img src="https://agentmods.dev/badge/skills/googilyboogily/googilyboogily-claude-power-tools/agent-audit.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 | $0.00057 | $0.01213 |
| Opus 5 | $0.00028 | $0.00607 |
| Sonnet 5 | $0.00011 | $0.00243 |
| Haiku 4.5 | $0.00006 | $0.00121 |
Grade A, and why
agent-audit 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 12d 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 — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Audit
Audit a Claude Code agent/subagent for quality, routing mesh compliance, and correctness. Each issue is presented one at a time with multiple resolution options, always including a research option that forks parallel code + web research agents.
Input
$ARGUMENTS — path to the agent .md file.
Parse Arguments
Extract from $ARGUMENTS:
- Agent Path: Path to the
.mdfile - Verify the file exists and has
.mdextension. If not found, report error and stop. - Extract agent name from filename (without
.mdextension).
Process
Phase 1: Load Documents
- Read the agent
.mdfile. - Read the audit checklist at
${CLAUDE_SKILL_DIR}/references/checklist.md. - Parse the frontmatter (YAML between
---delimiters) and body content separately. - Scan the agent's sibling directory for other agents (to check routing mesh references).
- Optionally scan other installed plugin agent directories to verify cross-delegation targets exist.
Phase 2: Run All Checks
Evaluate every check from the checklist against the loaded agent. For each check:
- Determine status: PASS, FAIL, or N/A
- For FAIL: record the severity and a specific description of what's wrong
Build a prioritized issue queue:
- 🔴 CRITICAL issues first
- 🟡 WARNING issues next
- 🔵 INFO issues last
- ❓ Open Questions last
Phase 3: Present Summary
## Agent Audit Summary: [agent name]
**File:** [path]
**Lines:** [line count]
**Routing Mesh:** [delegation targets found, if any]
Found **N issues** and **M open questions**:
- 🔴 CRITICAL: [count]
- 🟡 WARNING: [count]
- 🔵 INFO: [count]
- ❓ Open Questions: [count]
Starting sequential resolution...
If zero issues found, skip to Phase 5 with PASS verdict.
Phase 4: Sequential Resolution
For each issue, present using AskUserQuestion with:
- Clear description of the issue and which checklist item it violates
- At least 2 fix options (one marked ⭐ recommended)
- Always include "🔍 Research code & web" option
- Always include "Skip" as last option
What ships with it
1 file 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.
- 12d ago First seen · 164 lines · 57 tokens per session scan A 7dc2952c07be
agent-audit is a skill published in the GitHub repository GoogilyBoogily/googilyboogily-claude-power-tools (2 stars, last pushed 4mo ago), licensed MIT. It adds 57 tokens to every session and 1,213 once invoked, about $0.0003 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
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…