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NeptuneHubNeptuneHub/AudioMuse-AI/.github/skills/arch-review/SKILL.md

arch-review

Skill2.9k starsChanged 4 months agoAGPL-3.0View on GitHub

Scan the codebase for architectural friction and return an action plan - a ranked list of deepening opportunities, each scored for regression risk from 1 to 10, ordered by the value it adds. Refactors that turn shallow modules into deep ones, for testability and AI-navigability. Output is a markdown table plus pointed lists, never HTML and never a written report file. Use when the user asks where the codebase is getting hard to change, for refactoring opportunities, or for an architecture review.

7 other projects use a version of this.

Trending

Less talk lately.about the whole repository

Dec 2025: 2 mentionsJan 2026: 0 mentionsFeb 2026: 10 mentionsMar 2026: 2 mentionsApr 2026: 1 mentionMay 2026: 2 mentionsJun 2026: 3 mentionsJul 2026: 8 mentionsAug 2026: 1 mentionSep 2026: 4 mentionsOct 2026: 3 mentionsNov 2026: 1 mention
Dec 2025Jun 2026Nov 2026
Mentions a month of the NeptuneHub/AudioMuse-AI repository that our weekly crawl found. There is no adoption data for this file yet.

Most recently taken up by

Who's talking about NeptuneHub/AudioMuse-AI

The biggest 5 of 54 mentions linking to the repository that our crawl found. Each line is their own headline.

See all 54

Talked about on GitHub, Bluesky and Hacker News (54 times).

On GitHub · 46

41 more on GitHub

On Bluesky · 5

  • Other versions7 projects use a version of this.

    Word for word · 0

    None found.

    Edited · 0

    None found.

    Wrote their own version · 7

    1. axisrobo/ea-harness★ 15same name
    2. axisvela/ea-harness★ 15same name
    3. ramboz/jig★ 7same name
    4. AllThingsSmitty/proven-skills★ 1same name
    5. anxndsgn/skills★ 1same name
    6. newkirkjosh/skills★ 1same name
    7. rhvdbergh/claude-skills★ 0same name

    How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.

  • In this repository2 other files it gives its agents.

The file

We split this skill into the rules it gives an agent

9 rules. 0 are common, 8 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 7 edited versions we read keep these.

  • 8

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

Licensed with conditions — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

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