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brooks-lint

hyhmrright · hyhmrright/brooks-lint

Performs AI code reviews grounded in classic engineering books, diagnosing decay risks with citations, severity labels, and auto-fix capabilities.

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

1.5k stars69License: MITUpdated 13 days ago0 opens

Preview

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What you can do with it

  • Get an AI-driven code review for a new feature implementation.
  • Audit existing codebase architecture for potential technical debt.
  • Automatically fix minor code quality issues across a project.

Safety check

Caution

Usable, but read the notes first.

  • ●Installer downloads a remote script and pipes it to the shell.scripts/install.sh

Automated scan of the repo files. Always review code you run.

From the README

brooks-lint

AI code reviews grounded in twelve classic engineering books. Consistent. Traceable. Actionable.

English · 简体中文 · 繁體中文 · 日本語 · 한국어 · Español

Quick Start • The Six Decay Risks • What It Looks Like • Benchmark • Installation

→ Visit the website


"The bearing of a child takes nine months, no matter how many women are assigned." — Frederick Brooks, The Mythical Man-Month (1975)

50 years later, Brooks was still right — and so were McConnell, Fowler, Martin, Hunt & Thomas, Evans, Ousterhout, Winters, Meszaros, Osherove, Feathers, and the Google Testing team.

Most code quality tools count lines and cyclomatic complexity. brooks-lint goes deeper — it diagnoses your code against six decay risk dimensions synthesized from twelve classic engineering books, producing structured findings with book citations, severity labels, and concrete remedies every time.

For the full source-to-skill mapping, including exceptions and false-positive guards, see skills/_shared/source-coverage.md.

Quick Start

# Claude Code
/plugin marketplace add hyhmrright/brooks-lint
/plugin install brooks-lint@brooks-lint-marketplace

# Any other Agent Skills platform — Cursor · Codex · Gemini · Copilot · Windsurf · OpenCode · Kiro · Bob …
curl -fsSL https://raw.githubusercontent.com/hyhmrright/brooks-lint/main/scripts/install.sh | bash -s -- 

Then just ask ("review this PR", "audit the architecture"), or run one of the six commands — /brooks-review, /brooks-audit, /brooks-debt, /brooks-test, /brooks-health, /brooks-sweep (what each one does).

Every finding comes back as Symptom → Source → Consequence → Remedy with a book citation and a 0–100 Health Score. Full install options (10 more platforms) and CI/CD setup are below.

The Twelve Books

BookAuthorContributes to
The Mythical Man-Month (1975)Frederick P. Brooks Jr.R2, R4, R5
Code Complete (1993, 2nd ed. 2004)Steve McConnellR1, R4
Refactoring (1999, 2nd ed. 2018)Martin FowlerR1, R2, R3, R4, R6
Clean Architecture (2017)Robert C. MartinR2, R5
The Pragmatic Programmer (1999, 20th Anniv. 2019)Andrew Hunt & David ThomasR2, R3, R4, R5, T2, T3
Domain-Driven Design (2003)Eric EvansR1, R3, R6
A Philosophy of Software Design (2018)John OusterhoutR1, R4
Software Engineering at Google (2020)Winters, Manshreck & WrightR2, R5
The Art of Unit Testing (2009, 3rd ed. 2023)Roy OsheroveT1, T2, T4, T5
How Google Tests Software (2012)Whittaker, Arbon & CarolloT5, T6
Working Effectively with Legacy Code (2004)Michael FeathersT4, T5, T6
xUnit Test Patterns (2007)Gerard MeszarosT1, T2, T3, T4

The Six Decay Risks

brooks-lint evaluates your code across six production-code decay risks and six test-suite decay risks synthesized from twelve classic engineering books:

Decay RiskDiagnostic QuestionSources
🧠 Cognitive OverloadHow much mental effort to understand this?Code Complete, Refactoring, DDD, Philosophy of SD
🔗 Change PropagationHow many unrelated things break on one change?Refactoring, Clean Architecture, Pragmatic, SE@Google
📋 Knowledge DuplicationIs the same decision expressed in multiple places?Pragmatic, Refactoring, DDD
🌀 Accidental ComplexityIs the code more complex than the problem?Refactoring, Code Complete, Brooks, Philosophy of SD
🏗️ Dependency DisorderDo dependencies flow in a consistent direction?Clean Architecture, Brooks, Pragmatic, SE@Google
🗺️ Domain Model DistortionDoes the code faithfully represent the domain?DDD, Refactoring

Philosophy of SD = A Philosophy of Software Design (Ousterhout) · SE@Google = Software Engineering at Google (Winters et al.)

What It Looks Like

Given this code:

class UserService:
    def update_profile(self, user_id, name, email, avatar_url):
        user = self.db.query(f"SELECT * FROM users WHERE id = {user_id}")
        user['email'] = email
        ...
        if user['email'] != email:   # always False — silent bug
            self.smtp.send(...)
        points = user['login_count'] * 10 + 500
        self.db.execute(f"UPDATE loyalty SET points={points} WHERE user_id={user_id}")

brooks-lint produces:


Health Score: 28/100

This method concentrates four unrelated business responsibilities into a single function, contains a logic bug that silently suppresses email change notifications, and is wide open to SQL injection.

🔴 Change Propagation — Single Method Changes for Four Unrelated Business Reasons

Symptom: update_profile performs profile field updates, email change notifications, loyalty points recalculation, and cache invalidation all in one method body. Source: Fowler — Refactoring — Divergent Change; Hunt & Thomas — The Pragmatic Programmer — Orthogonality Consequence: Any change to the loyalty formula risks breaking email notifications and vice versa. Every edit carries regression risk across four unrelated domains simultaneously. Remedy: Extract NotificationService, LoyaltyService, and UserCacheInvalidator. UserService.update_profile should orchestrate by calling each — it should hold no implementation logic itself.

🔴 Domain Model Distortion — Silent Logic Bug: Email Notification Never Fires

Symptom: user['email'] = email overwrites the old value before if user['email'] != email — the condition is always False. The notification is dead code. Source: McConnell — Code Complete — Ch. 17: Unusual Control Structures Consequence: Users are never notified when their email address chan

View source on GitHub