Agent skill · Code Review & Quality

code-review-and-quality

Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.

Nick44,086★ · +407/wk · 1 repos on radarProfile →
claude-codecodexcursorMIT
Install
npx skills add sickn33/agentic-awesome-skills --skill code-review-and-quality --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 19 KB
Bundled scripts: none
Path: skills/code-review-and-quality/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 44,414 · +328 this week
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

Review
written from the skill's own SKILL.md · Aug 5, 2026

What it does

Conducts multi-axis code review across five axes: correctness, readability, architecture, security, and performance. Requires approving a change only if it definitively improves overall code health, even if not perfect. Used before merging any PR or change, after feature completion, when code from any source needs evaluation, or after bug fixes.

How it works

  • Evaluates code across five axes: Correctness, Readability & Simplicity, Architecture, Security, and Performance.
  • For Correctness: checks spec alignment, edge cases, error paths, test quality, and potential concurrency or state issues.
  • For Readability: assesses descriptive naming, straightforward control flow, logical organization, potential simplifications, and whether the code could be shorter without loss of clarity.
  • For Architecture: ensures consistency with patterns, module boundaries, duplication, dependency direction, and appropriate abstraction level.
  • For Security: checks input handling, secret exposure, authentication/authorization, parameterized queries, output encoding, dependencies, and handling of external data as untrusted.
  • For Performance: looks for N+1 patterns, unbounded loops, async handling, unnecessary re-renders, pagination concerns, and large objects in hot paths.
  • Includes guidance on structural remedies, change sizing, and a multi-model review pattern to separate concerns between models and humans.
  • Provides a detailed review process: understand context, review tests first, then implementation, and categorize findings with severity labels.
  • Emphasizes dead code hygiene and a fast review cadence to minimize delays.

When to use it

  • Before merging any PR or change
  • After completing a feature implementation
  • When code from another agent or human needs evaluation
  • After refactoring or bug fixes to assess regressions

What it can touch

  • The skill operates on code quality and review process; it references tools and patterns rather than executing external actions. The skill mentions review patterns, testing, and verification steps but does not enumerate file paths or commands the agent must directly run in this summary. It directs the reviewer to consider tests, build status, and manual verification as part of the workflow.

Caveats

  • Declared risk: critical
  • License: MIT
  • No explicit promises about automated fixes or outcomes; the guidance is to approve only when improvements to code health are evident and aligned with project conventions. The review framework emphasizes explicit verification steps and categorization of findings (Critical, Required, Optional, Nit).
From the SKILL.md

# Code Review and Quality ## Overview Multi-dimensional code review with quality gates. Every change gets reviewed before merge — no exceptions. Review covers five axes: correctness, readability, architecture, security, and performance. **The approval standard:** Approve a change when it definitely improves overall code health, even if it isn't perfect. Perfect code doesn't exist — the goal is continuous improvement. Don't block a change because it isn't exactly how you would have written it. If it improves the codebase and follows the project's conventions, approve it. ## When to Use - Before merging any PR or change - After completing a feature implementation - When another agent or model produced code you need to evaluate - When refactoring existing code - After any bug fix (review both the fix and the regression test) ## The Five-Axis Review Every review evaluates code across these dimensions: ### 1. Correctness Does the code do what it claims to do? - Does it match the spec or task requirements? - Are edge cases handled (null, empty, boundary values)? - Are error paths handled (not just the happy path)? - Does it pass all tests? Are the tests actually testing the right things?

What's inside
Steps it walks through
  1. Overview
  2. When to Use
  3. The Five-Axis Review
  4. 1. Correctness
  5. 2. Readability & Simplicity
  6. 3. Architecture
  7. 4. Security
  8. 5. Performance
  9. Structural Remedies
  10. Change Sizing
  11. Change Descriptions
  12. Review Process
  13. Step 1: Understand the Context
  14. Step 2: Review the Tests First
More from agentic-awesome-skills
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About this skill
What does the code-review-and-quality skill do?

Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.

How do I install it?

Run `npx skills add sickn33/agentic-awesome-skills --skill code-review-and-quality --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From sickn33/agentic-awesome-skills, a repository with 44,414 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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