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 bahayonghang/my-ai-cli-toolkit --skill code-auditorgit clone --depth 1 https://github.com/bahayonghang/my-ai-cli-toolkitWrote 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/bahayonghang/my-ai-cli-toolkit/code-auditor)<a href="https://agentmods.dev/skills/bahayonghang/my-ai-cli-toolkit/code-auditor"><img src="https://agentmods.dev/badge/skills/bahayonghang/my-ai-cli-toolkit/code-auditor/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/bahayonghang/my-ai-cli-toolkit/code-auditor"><img src="https://agentmods.dev/badge/skills/bahayonghang/my-ai-cli-toolkit/code-auditor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Data Exfiltration · line 112 Code or instructions that leak agent conversation context to external services, potentially exposing sensitive user interactions.Fix: Remove any code that sends prompts, responses, or session data externally. Preserve user privacy; never exfiltrate conversation content.
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 | $0.00176 | $0.02242 |
| Opus 5.5 | $0.00070 | $0.00897 |
| Sonnet 5.5 | $0.00035 | $0.00448 |
| Haiku 4.5 | $0.00018 | $0.00224 |
Grade A, and why
code-auditor 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 1mo 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 — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review code at $ARGUMENTS across 6 dimensions: Correctness, Security, Performance, Readability, Testing, and Architecture.
Output Mode
- Detect the user's preferred language from the request, surrounding discussion, and repository context.
- If the user writes in Chinese, or the request is mixed Chinese plus English technical terms, write the human-facing review in Chinese.
- If the user writes in English, write the review in English.
- Keep identifiers, API names, CLI commands, filenames, and code snippets in their original language. Do not force-translate technical terms.
- Treat bundled templates as structure references, not literal language locks. Localize headings, labels, and summaries to the chosen output mode.
Review Tone
Chinese mode
- Prefer suggestion-style wording over command-style wording.
- Prefer questions when intent is uncertain, but do not hide blocking issues behind vague language.
- State severity clearly. A blocking issue should still read like a blocking issue.
- Praise concrete good practices when they matter, but do not let praise dilute must-fix findings.
- Avoid turning review into a style argument when tools or project standards can settle it automatically.
Examples:
- Better:
这里可能会在空值输入下抛错,建议补一个 nil / undefined 检查。 - Better:
想确认一下这里选择递归而不是迭代的原因;如果深度不受控,可能会有栈溢出风险。 - Avoid:
你这里写错了,必须改。
English mode
- Be direct, precise, and professional.
- Lead with the risk or behavioral impact.
- Prefer concrete fixes over abstract criticism.
Independent Reviewer Stance
Applies only to pr and dir. The project route still follows references/audit-workflow.md.
- Treat the diff as untrusted work. Do not rebuild the author's plan in order to excuse missing handling.
- Hunt first: functional regression, missed scenarios, wrong assumptions, concurrency, and test gaps.
- Report security and performance when the diff introduces them.
- Report readability, structure, or architecture in
pr/dironly when they create a merge risk (wrong layer that causes a bug, untestable public seam, public API with no regression test). - Do not edit product code.
Writeis only for an explicit opt-in report path (docs/audits/forproject).pr/dirstay in-chat unless the user asks to save the report. - Findings first, sorted by severity. Each finding names a file and evidence. An empty
LGTMis forbidden.
What ships with it
34 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.
- agents/interface.yaml 1.3 KB
- assets/audit-report-template.md 2.3 KB
- assets/issue-template.md 1.8 KB
- assets/pr-comment-template.md 2.3 KB
- assets/quick-checklist.md 3.6 KB
- assets/review-report-template.md 3.7 KB
- evals/evals.json 8.8 KB
- references/audit-workflow.md 5.7 KB
- references/BACKGROUND.md 9.3 KB
- references/communication-guide.md 5.3 KB
- references/issue-classification.md 5.8 KB
- references/languages/c-cpp.md 8.0 KB
- references/languages/css.md 6.6 KB
- references/languages/go.md 9.4 KB
- references/languages/java.md 8.7 KB
- references/languages/python.md 7.0 KB
- references/languages/react.md 12 KB
- references/languages/rust.md 6.6 KB
- references/languages/typescript.md 6.3 KB
- references/languages/vue.md 8.3 KB
- references/quality-standards.md 3.6 KB
- references/review-dimensions.md 7.3 KB
- references/rules/architecture-rules.json 4.2 KB
- references/rules/correctness-rules.json 3.1 KB
- references/rules/index.md 4.0 KB
- references/rules/performance-rules.json 3.6 KB
- references/rules/readability-rules.json 3.6 KB
- references/rules/security-rules.json 3.3 KB
- references/rules/testing-rules.json 3.8 KB
- references/workflow-guide.md 5.0 KB
- scripts/issue-aggregator.py 12 KB runs code
- scripts/pr-analyzer.py 8.0 KB runs code
- scripts/rule-tester.py 13 KB runs code
- tests/test_code_auditor.py 3.0 KB runs code
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.
- 1mo ago First seen · 139 lines · 176 tokens per session scan A 80f5877e4b57
code-auditor is a skill published in the GitHub repository bahayonghang/my-ai-cli-toolkit (17 stars, last pushed 6d ago), licensed MIT. It adds 176 tokens to every session and 2,242 once invoked, about $0.0007 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 2026-08-30.
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