Code Quality Review
SkillDev toolsRun an extremely strict maintainability and structural code quality review, flags abstraction issues, spaghetti growth, and boundary leaks
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Code Quality Review skill
What this skill tells your AI
The instructions your AI receives, as published by jellydn/my-ai-tools in skills/code-quality-review/SKILL.md and read by ahel’s 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:
- Simpler structure — Can a different model or ownership boundary remove branches, modes, helpers, or layers?
- Cohesive control flow — Flag scattered special cases, repeated conditions, deep nesting, and mixed responsibilities.
- Useful abstractions — Flag thin wrappers, generic magic, speculative extension points, and duplicate helpers.
- Clean boundaries — Keep feature logic in its canonical module and make types and invariants explicit.
- Reasonable file size — Treat a change that pushes a file above 1,000 lines as a decomposition signal unless the file has a clear structural reason to stay whole.
- Sound orchestration — Flag unnecessarily sequential independent work and updates that can leave related state partially applied when a clearer atomic design exists.
- Legibility — Prefer direct, boring code with clear names and comments that explain only non-obvious reasons.
Finding Bar
Report a finding only when you can name:
- the file and relevant hunk;
- the concrete maintenance cost or failure mode;
- the smallest practical remedy; and
- why the remedy is better than the current design.
Treat these as blockers unless the implementation has a clear justification:
- a structural regression or avoidable boundary leak;
- a file newly crossing 1,000 lines without useful decomposition;
- ad hoc branching added to an already busy flow;
- duplicated logic where a canonical helper exists;
- an abstraction, cast, or optional contract that adds indirection without clarity; or
- a clear simplification that removes substantial incidental complexity.
Do not block on personal style, hypothetical future needs, or a rewrite that is only differently complex.
Output
Order findings by impact:
- Structural regressions and simpler designs
- Control-flow, boundary, abstraction, and type problems
- File-size, modularity, and legibility concerns
For each finding, use:
[severity] file:line — finding
Impact: concrete cost or risk
Fix: smallest practical remedy
End with APPROVE when no blocking finding remains, or CHANGES REQUESTED with the blocker count. Be direct and
respectful.
Signals
- GitHub stars
- 120
- Forks
- 13
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
code-quality-review-jellydn- Source
- github.com/jellydn/my-ai-tools