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 yuexueyu/anna-agent-skills --skill code-auditgit clone --depth 1 https://github.com/yuexueyu/anna-agent-skillsWrote 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/yuexueyu/anna-agent-skills/code-audit)<a href="https://agentmods.dev/skills/yuexueyu/anna-agent-skills/code-audit"><img src="https://agentmods.dev/badge/skills/yuexueyu/anna-agent-skills/code-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/yuexueyu/anna-agent-skills/code-audit"><img src="https://agentmods.dev/badge/skills/yuexueyu/anna-agent-skills/code-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 | $0.00080 | $0.04947 |
| Opus 5 | $0.00040 | $0.02474 |
| Sonnet 5 | $0.00016 | $0.00989 |
| Haiku 4.5 | $0.00008 | $0.00495 |
Grade C, and why
code-audit scanned grade C with 3 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 9d 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.
Cloud metadata endpointmediumServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
17. 云/容器安全:特权容器、密钥在环境变量中明文、IMDS(169.254.169.254)可访问 Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Recursive force deletemediumDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
| **Shell** | `rm -rf $var/` (var可能为空) | 删根目录 | `rm -rf "${var:?}/"` | Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
- **注入类**: `exec(`, `eval(`, `system(`, `Runtime.exec`, `os.system`, `NSTask`, `Process(` The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 9d ago First seen · 280 lines · 80 tokens per session scan C 89d0207c7b31
code-audit is a skill published in the GitHub repository yuexueyu/anna-agent-skills (3 stars, last pushed 5mo ago), with no licence file. It adds 80 tokens to every session and 4,947 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it C with 3 findings (cloud metadata endpoint, recursive force delete, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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omh-code-review
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revdiff-plan
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code-reviewer
Code review specialist focused on patterns, bugs, security, and performance.
agent-teams-simplify-and-harden
Implementation + audit loop using parallel agent teams with structured simplify, harden, and document passes. Spawns implementation agents to do the work, then audit agents to find complexity, security gaps, and spec deviations, then loops until code compiles cleanly, all tests pass, and auditors find zero issues or…