hyhmrright/brooks-lint
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 observed · 2026-08-28
Health v2 · maintenance only
81/100
- Activity 99
- Release rhythm 98
- Longevity 11
Flags: young
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: 1
- age_days: 160
- days_rel: 19
- days_push: 9
- n_releases_24m: 32
Adoption not part of the score
1418 stars · 64 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
brooks-lint is an AI-powered code review plugin for Claude Code, Codex CLI, and Gemini CLI that diagnoses code against six decay risk dimensions synthesized from twelve classic software engineering books. It produces structured findings with book citations, severity labels, health scores, and concrete remedies, including a full-sweep mode that auto-fixes issues.
Use cases
- review pull requests with AI grounded in classic engineering principles
- audit codebase architecture for dependency and complexity problems
- identify and prioritize technical debt with severity labels
- assess test suite quality and detect test decay
- generate a code health dashboard with a numeric score
- automatically fix code smells and architectural drift
- get cited explanations for why code is hard to maintain
When to choose
- you use Claude Code, Codex CLI, or Gemini CLI and want structured, citation-backed code reviews
- you need to diagnose architectural drift, knowledge duplication, or accidental complexity beyond what linters catch
- you want consistent review output with a fixed Symptom → Source → Consequence → Remedy format
- you want language-agnostic code quality analysis with zero configuration
When to avoid
- you need traditional deterministic linting with precise syntax rules
- you don't use any supported AI coding CLI and can't run LLM-based analysis
- you require guaranteed correctness of automated fixes without human review
- you need CI-native static analysis with low latency and no AI costs
Facets
plugin · maturity active
code-review linter developer-tools llm-inference prompt-engineering developer-tools cli cross-platform ai-code-review claude-code-plugin codex-cli-plugin gemini-cli-extension tech-debt architecture-review code-smells refactoring test-quality auto-fix agent-skills book-citations code-review software-quality automation
2 sources
- readme: https://github.com/hyhmrright/brooks-lint · fetched 2026-08-28 · a612d6fb9492
- homepage: https://hyhmrright.github.io/brooks-lint/ · fetched 2026-08-29 · f146063df58d
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| hyhmrright/brooks-lint | main | 81 |
For agents
markdown · JSON · MCP: product_card(name="hyhmrright/brooks-lint")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem