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Brooks-Lint

AI code reviews grounded in 12 classic engineering books

Details

External ID
48490591
Source
HN
Company
—
Product
Brooks-Lint
Website domain
github.com
Launched
June 11, 2026
Cohort
—
Upvotes
8
Upvotes percentile
0.4952185792349727
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

I once managed a small team and hired an intern to develop the backend services for a software system. He used AI tools to write the entire project; while it ran correctly and produced the right results, the directory structure was atrocious upon review. Typically, a FastAPI service is organized into components like routers and services, but he had created an unnecessarily deep, multi-layered structure within the service layer—logic that should have simply been split across two or three files. The code lacked elegance. Recalling concepts from books on software project management, code structure, and architecture—such as The Mythical Man-Month—I decided to codify these architectural principles into a reusable "skill" to optimize my project's structure. I used Claude Code to create a skill called `brooks-lint` and employed it to refactor the project, resulting in a much clearer and more logical architecture. I encourage everyone to use this skill, identify issues, submit pull requests, and collaborate on improvements, thereby benefiting the projects you are currently developing.

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI-native
Project type
Commercial product
Normalized one-liner
ai code review based on engineering best practices
Manually corrected
False

Could you build this?

Yes It is a static analysis or LLM prompt wrapper that evaluates codebase structure and PR diffs against established architectural principles and software engineering literature.

Discussion

1 comment analyzed.

Competitors

Other products that read as similar to this one — 127 launches clear the similarity bar, closest 8 shown.

Attention rank: #59 of 128 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 222 days after the earliest competitor.

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