brooks-lint — AI Code Review That Cites the Canon
Author: Björn Schotte (LinkedIn) URL: https://www.linkedin.com/posts/bjoernschotte_aicodereview-harnessengineering-claudecode-share-7469996798825246720-YgXD/
What It Is
An AI code review tool called brooks-lint — every finding cites the book it came from: Brooks, Fowler, Martin, Feathers — twelve software engineering classics in all.
How It Works
It distills those books into:
- 6 production-code decay risks — cognitive overload, change propagation, dependency disorder, accidental complexity
- 6 test-suite risks — (matching decay patterns)
Each finding lands in a structured format:
Symptom → Source → Consequence → Remedy
Tagged with a severity label and a 0–100 health score.
Architecture Audit Mode
Draws a Mermaid dependency graph, color-coded by severity.
Platform Support
Ships as:
- Claude Code plugin
- Codex CLI skill
- Gemini CLI extension
- GitHub Action
License: MIT Stars: 532 in ten weeks
The Benchmark
Across three review scenarios:
- With brooks-lint: structured and sourced findings 94% of the time
- Without (same model unguided): 16% of the time
The Insight
“The model already knows the canon. The harness makes it cite the canon — every finding, every run. On AI review the bottleneck was never detection. It’s whether you can trust the same answer twice.”