Home / jellydn / my-ai-tools · configs/amp/plugins/my-ai-tools-skills/skills/code-quality-review/SKILL.md · GitHub

code-quality-review skillA

code-quality-review is agent-read markdown (skill) from jellydn/my-ai-tools: Audit a diff for structural maintainability and unnecessary complexity..

Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.

What the file says

# Code Quality Review

Review the current branch diff for structural quality. Preserve behavior, but actively look for a simpler design that
deletes concepts, branches, wrappers, or layers instead of moving complexity around.

## Review Boundaries

- Review only the changed code and the surrounding code needed to judge it.
- Treat repository conventions and existing canonical helpers as the source of truth.
- Skip formatter and linter findings that automation already reports.
- Prefer a small set of high-confidence structural findings over cosmetic notes.
- Do not propose a large refactor unless its benefit is clear and it stays within the change's ownership boundary.

## Review Criteria

Check each meaningful change for:

1. **Simpler structure** — Can a different model or ownership boundary remove branches, modes, helpers, or layers?
2. **Cohesive control flow** — Flag scattered special cases, repeated conditions, deep nesting, and mixed responsibilities.
3. **Useful abstractions** — Flag thin wrappers, generic magic, speculative extension points, and duplicate helpers.
4. **Clean boundaries** — Keep feature logic in its canonical module and make types and invariants explicit.
…

Read the whole file at its exact version.

How to install

Latest version
mdr add jellydn/my-ai-tools/code-quality-review@git:20260913.e2e25be
Exact content
mdr add jellydn/my-ai-tools/code-quality-review@sha256:131c36456448b57b

Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_eo7gg2hqsusmd3pp.svg)](https://markdownregistry.com/a/art_eo7gg2hqsusmd3pp)

1 badge views in 30 days

Versions

versioncommittedcommitsizeaudit
git:20260913.e2e25be latest2026-09-13 e2e25be 3,283 BA view · diff
git:20260814.d1987f52026-08-14 d1987f5 12,678 BA view

Audit of the latest version

A  17 of 17 checks passed. Deterministic, no model, same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (3283 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

jellydn/my-ai-tools · 121 stars · license MIT · pushed 2026-09-24 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_eo7gg2hqsusmd3pp
GET https://markdownregistry.com/api/v1/resolve?ref=jellydn/my-ai-tools/code-quality-review
GET https://markdownregistry.com/api/v1/blob/131c36456448b57b07ef875647469c400a411d1ccad7e9697f5e0ffa9f79f2b7

Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

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