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Testing107k · #343

code-review-and-quality

Performs detailed code reviews on multiple fronts. It's useful before merging new changes to ensure quality and prevent future problems.

What it does

This tool reviews your code to ensure it's correct, easy to understand, well-organized, secure, and fast. It helps find issues before the code is added to the main project.

When to use it

  • ✓Before adding a code change to the project.
  • ✓When you want to check the quality of code written by yourself or someone else.
  • ✓After fixing a bug or adding a new feature.

Example of what to ask your AI

“Review this code to ensure it is correct, readable, secure, and performs well.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/addyosmani/agent-skills/blob/main/skills/code-review-and-quality/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/addyosmani/agent-skills/blob/main/skills/code-review-and-quality/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool analyzes the code in five areas: whether it does what it's supposed to (correctness), if it's easy to read (readability), if it fits the project's structure (architecture), if it's safe from attacks (security), and if it's not slow (performance).

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add addyosmani/agent-skills --skill code-review-and-quality

Or download just the file:

curl -L https://raw.githubusercontent.com/addyosmani/agent-skills/main/skills/code-review-and-quality/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

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?
  • Are there off-by-one errors, race conditions, or state inconsistencies?

2. Readability & Simplicity

Can another engineer (or agent) understand this code without the author explaining it?

  • Are names descriptive and consistent with project conventions? (No temp, data, result without context)
  • Is the control flow straightforward (avoid nested ternaries, deep callbacks)?
  • Is the code organized logically (related code grouped, clear module boundaries)?
  • Are there any "clever" tricks that should be simplified?
  • Could this be done in fewer lines? (1000 lines where 100 suffice is a failure)
  • Are abstractions earning their complexity? (Don't generalize until the third use case)
  • Would comments help clarify non-obvious intent? (But don't comment obvious code.)
  • Are there dead code artifacts: no-op variables (_unused), backwards-compat shims, or // removed comments?
  • Is a new conditional bolted onto an unrelated flow? That's a design smell, not a nit — push the logic into its own helper, state, or policy instead of tangling an existing path.
  • Do repeated conditionals on the same shape appear? They signal a missing model or dispatcher. A "temporary" branch is usually permanent debt.

3. Architecture

Does the change fit the system's design?

  • Does it follow existing patterns or introduce a new one? If new, is it justified?
  • Does it maintain clean module boundaries?
  • Is there code duplication that should be shared?
  • Are dependencies flowing in the right direction (no circular dependencies)?
  • Is the abstraction level appropriate (not over-engineered, not too coupled)?
  • Does this refactor reduce complexity or just relocate it? Count the concepts a reader must hold to follow the change. If a "cleaner" version leaves that count unchanged, it isn't cleaner — prefer the restructuring that makes whole branches, modes, or layers disappear over one that re-centralizes the same logic. Prefer deleting an abstraction to polishing it.
  • Is feature-specific logic leaking into a shared or general-purpose module? Keep logic in its owning layer, reuse the existing canonical helper instead of a near-duplicate, and don't normalize architectural drift.
  • Are type boundaries explicit? Question gratuitous any/unknown/optional/casts and silent fallbacks that paper over an unclear invariant — making the boundary explicit often makes the surrounding control flow simpler.

4. Security

For detailed security guidance, see security-and-hardening. Does the change introduce vulnerabilities?

  • Is user input validated and sanitized?
  • Are secrets kept out of code, logs, and version control?
  • Is authentication/authorization checked where needed?
  • Are SQL queries parameterized (no string concatenation)?
  • Are outputs encoded to prevent XSS?
  • Are dependencies from trusted sources with no known vulnerabilities?
  • Is data from external sources (APIs, logs, user content, config files) treated as untrusted?
  • Are external data flows validated at system boundaries before use in logic or rendering?

5. Performance

For detailed profiling and optimization, see performance-optimization. Does the change introduce performance problems?

  • Any N+1 query patterns?

…

FAQ

What does 'multi-axis review' mean?

It means the code is evaluated across several important areas, like correctness, clarity, security, and performance, rather than just one aspect.

Does the code need to be perfect?

No, the goal is continuous improvement. The code should improve overall quality, even if it's not perfect or written exactly how you would write it.

What should I do if the review finds problems?

The tool suggests how to fix issues, such as simplifying the code, separating complex parts, or ensuring security is maintained.

Details

Original description by the author

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. Use when asked to review a diff or a pull request, even when the diff is pasted inline.

repo: addyosmani/agent-skills

Popularity

GitHub stars
107k
Ranking position
#343
License
MIT
Updated
10/13/2026

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