No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by hyhmrright · Codex Skill · ★ 1.5k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is brooks-lint safe to install? View the security audit →
brooks-lint AI code reviews grounded in twelve classic engineering books. Consistent. Traceable. Actionable. English · 简体中文 The Six Decay Risks • What It Looks Like • Benchmark • Installation → Visit the website "The bearing of a child takes ni
| Stars | 1,500 |
| Forks | 68 |
| Language | HTML |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 66.9406265874117/100 |
| Last Updated | 2026-09-28 |
| Created | 2026-03-26 |
| Platforms | claude-code, cli, codex, gemini |
| Est. Tokens | ~22k |
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brooks-lint is AI code reviews grounded in 12 classic engineering books — decay risk diagnostics with book citations, severity labels, and 6 analysis modes including full-sweep auto-fix. It is categorized as a Codex Skill with 1.5k GitHub stars.
brooks-lint is primarily written in HTML. It covers topics such as agent-skills, ai-code-review, architecture-review.
You can find installation instructions and usage details in the brooks-lint GitHub repository at github.com/hyhmrright/brooks-lint. The project has 1.5k stars and 68 forks, indicating an active community.
brooks-lint is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to brooks-lint on Agent Skills Hub include claude-code-workflows, repowise, pilot-shell. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: