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None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 50 |
| Forks | 5 |
| Language | Python |
| Category | AI Tool |
| Quality Score | 50/100 |
| Last Updated | 2026-03-25 |
| Created | 2026-03-20 |
| Platforms | python |
| Est. Tokens | ~2k |
Code Review Skill 自动化代码审核技能，适用于通用代码工程的定期代码质量审查。 快速开始 首次运行时，如果不存在 ，会交互式询问审核参数。后续运行自动读取配置。 工作流程 配置文件 路径： jsonc { "target": { "directories": [""], // 审核目标目录 "fileextensions": [".cs"], // 目标文件后缀 "excludedirectories": [""], // 排除目录 "excludefilepatterns": [".meta", ".Designer.cs"] // 排除文件模式 }, "git": { "since": "2026-01-17", // git log 起始日期 "branch": "" // 空 = 当前分支 }, "review": { "maxfilespermodule":...
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: