Code Quality Review

SkillProductivity

Lets your agent review code changes for correctness, regression risk, and unnecessary complexity.

Available today. Use it from your connected AI after setup.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Code Quality Review skill

About this skill

Review a task-owned diff for correctness, regression risk, and unnecessary complexity when a quality review is requested or called for by repository policy.

What this skill tells your AI

The instructions your AI receives, as published by bitsocialnet/5chan in .agents/skills/code-quality-review/SKILL.md and read by ahel’s review.

Review against the user's base, or the task's base branch plus its relevant staged, unstaged, and untracked changes. Preserve unrelated work. Read nearby source, changed tests, and applicable repository guidance before judging a hunk.

Focus on evidence-backed bugs, error paths, races, state consistency, trust boundaries, and concrete verification gaps. Challenge each finding against the implementation and intended behavior. Apply architecture and performance guidance only where the changed flow makes it relevant; when files or imports moved, run yarn boundaries instead of judging the module boundaries in src/AGENTS.md by eye.

For simplification, use the repository's solution ladder: remove unnecessary work, reuse existing code or platform facilities, and only then introduce new code. Do not trade away correctness, accessibility, validation, error handling, or useful tests. Preserve an unfamiliar guard or workaround until its purpose is understood.

Return actionable findings with file/line evidence, impact, and a practical correction, prioritized by risk. Skip tooling-handled style nits and speculative cleanup; if none remain, say so without a canned approval or publishing instruction.

A review-only request returns findings without edits. During an authorized implementation, apply high-confidence in-scope fixes without asking again for that authorization. This is an advisory pass, not an extra approval gate. Reuse verification evidence for the same final state; consult docs/agent-playbooks/verification.md only when a change or concrete uncertainty calls for more checks.

When a substantive review correction exposes a preventable mistake, use retro to identify useful prevention. Keep review-only requests read-only and reuse existing coverage where sufficient.

For an explicitly scoped semantic second opinion, use Jev diff review via the repository root. Select only relevant changed files and rules; the helper is opt-in, sends selected content only with --live, and returns advisory issues or uncertainty. Keep deterministic lint/tests and independent review authoritative. Do not wire it into automatic edit, commit, or repair hooks.

Signals

GitHub stars
132
Forks
14
Last commit
Sep 2026
Advanced
Catalog kind
skill
Key
code-quality-review
Source
github.com/bitsocialnet/5chan