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.
The code-review-and-quality skill provides a structured, multi-axis review process designed to evaluate code changes before they are merged into the main branch. It helps teams and AI-assisted development workflows maintain consistent engineering standards by reviewing every change across correctness, readability, architecture, security, and performance. The skill is intended to reduce regressions, improve maintainability, and ensure that code changes strengthen overall code health rather than simply meeting minimum functional requirements. Its review philosophy emphasizes continuous improvement over perfection, encouraging approvals for meaningful progress while still identifying important risks and weaknesses.
The skill evaluates code using a comprehensive five-axis framework. Correctness checks verify that implementations satisfy specifications, handle edge cases, and properly test expected behavior. Readability and simplicity reviews focus on maintainable naming, straightforward control flow, logical organization, and avoiding unnecessary abstractions or dead code. Architecture analysis ensures changes align with existing system patterns, maintain module boundaries, and avoid excessive coupling or duplication. Security review covers input validation, secret handling, authentication concerns, safe database interactions, trusted dependencies, and validation of external data flows. Performance review identifies inefficient query patterns, blocking operations, unbounded loops, unnecessary rendering, missing pagination, and memory-heavy operations in critical paths. The skill also promotes smaller, focused changes that are easier to review and deploy safely.
This skill is useful for software engineers, reviewers, technical leads, AI coding agents, and teams practicing collaborative or automated development workflows. It can be applied before merging pull requests, after feature implementations, during refactoring efforts, and following bug fixes to review both the fix and associated regression tests. The structured review model makes it suitable for projects that require consistent quality standards across human-written and AI-generated code.
This skill should be used before merging any code change, after implementing new features, during refactoring, and after bug fixes to review both the implementation and regression tests.
The review evaluates code across five dimensions: correctness, readability and simplicity, architecture, security, and performance.
No. The review principles are general and can be applied across different languages, frameworks, and project types as long as code quality and maintainability are relevant.
No. The approval standard focuses on whether a change improves overall code health and follows project conventions, rather than requiring a perfect implementation.
The guidance recommends small and focused changes, with approximately 100 lines changed considered a good target for easier review, safer deployment, and faster merging.
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