improve-codebase-architecture

Solid

Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.

AI & Automation 1 stars 0 forks Updated today MIT

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Quality Score: 80/100

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10
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
80
License 10%
100
Description 5%
100

Skill Content

# Improve Codebase Architecture Surface architectural friction and propose **deepening opportunities** — refactors that turn shallow modules into deep ones. The aim is testability and AI-navigability. Built on a shared design vocabulary: run the `codebase-design` skill for the architecture vocabulary (**module**, **interface**, **depth**, **seam**, **adapter**, **leverage**, **locality**) and its principles (the deletion test, "the interface is the test surface", "one adapter = hypothetical seam, two = real"). Use these terms exactly in every suggestion — don't drift into "component," "service," "API," or "boundary." Where the project keeps a domain glossary (an `AGENTS.md` glossary section or `CONCEPTS.md`), its terms give names to good seams. ## Process ### 1. Explore **Scope before you scan — YAGNI.** Deepening a module pays off by making future changes to it easier, so put extra weight on the parts of the codebase that have recently changed. Decide _where_ to look before you look: - If the user named a direction — a module, a subsystem, a pain point — take it, and skip the inference below. - Otherwise, walk back a good stretch of the commit history (`git log --oneline`) to find the codebase's hot spots — the files and areas that keep coming up — and let those paths pull your attention first. If the changes are scattered with no clear hot spot, widen the net. Read the project's domain glossary first, and search `docs/solutions/` for learnings and recorded rejectio...

Details

Author
toverux
Repository
toverux/grimoire
Created
2 weeks ago
Last Updated
today
Language
Shell
License
MIT

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