Brooks-Lint — PR Review
SkillMediaPR code review that surfaces decay risks, design smells, and maintainability issues with concrete Symptom → Source → Consequence → Remedy findings, drawing on twelve classic engineering books. Triggers when: user asks to review code, check a PR, shares a diff or pastes code asking "does this look right?" / "any issues here?" / "ready to merge?", or asks for feedback on a function, class, or file. Also triggers when user mentions: code smells / refactoring / clean architecture / DDD / SOLID principles / Hyrum's Law / deep modules / tactical programming / conceptual integrity / Brooks's Law / Mythical Man-Month / second system effect. Do NOT trigger for: questions about how to write code from scratch, language syntax questions, or framework/tool questions where no existing code is shared.
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Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Brooks-Lint — PR Review skill
What this skill tells your AI
The instructions your AI receives, as published by hyhmrright/brooks-lint in skills/brooks-review/SKILL.md and read by ahel’s review.
Setup
Read in order:
../_shared/common.md— Iron Law, Project Config, Report Template, Health Score../_shared/source-coverage.md— book coverage, exceptions, tradeoffs../_shared/decay-risks.md— symptom definitions and source attributionspr-review-guide.md(this directory) — the analysis process
Process
Scope: if the user did not specify files or paste code, apply Auto Scope Detection
(../_shared/common.md) first.
- Understand the review scope, then scan for each decay risk in the order specified (Steps 1–6 of the guide)
- Run the Quick Test Check (Step 7 of the guide) — skip for docs-only or non-production changes
- Apply the Iron Law to every finding
- Output using the Report Template from common.md
Mode line in report: PR Review
Signals
- GitHub stars
- 1k
- Forks
- 66
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
brooks-review- Source
- github.com/hyhmrright/brooks-lint