code-review
Systematic code review checklist
Skills matching the name, description or GitHub author.
Systematic code review checklist
Systematic code review guidance and automation. Apply TRUST 5 principles, check code quality, validate SOLID principles, identify security issues, and ensure maintainability. Use when conducting code reviews, s...
Automated code review with SOLID principles, code smells, and language-specific best practices.
Use this agent when you need to review code changes in a pull request or after writing/modifying code. The agent performs comprehensive code review following established team standards, categorizing findings as...
Provides comprehensive code review checklist following team standards. Use when reviewing pull requests or preparing code for review.
Comprehensive code review standards covering security, quality, performance, testing, and documentation. Includes checklists, common issues, and best practices for thorough code reviews.
Comprehensive code review skill for FastAPI projects. Analyzes codebase against industry best practices covering async patterns, project structure, Pydantic usage, dependency injection, database patterns, testi...
Comprehensive Go code review skill for PR reviews, architecture assessment, and test quality analysis. Use when reviewing Go code to ensure adherence to Go best practices, security standards, and project-specif...
Teetsh frontend code review for React/TypeScript PRs. Reviews component architecture, React Query, twin.macro styling, i18n, accessibility, responsive design, and testing. Use for PR reviews to ensure adherence...
This skill should be used when conducting focused code reviews that emphasize clarity, data flow understanding, and minimal assumptions. Trigger when reviewing pull requests, code changes, or when explicitly as...
Use this when user requests code review, pull request analysis, or quality assessment. Provides systematic 6-category checklist: functionality, security (OWASP), code quality (SOLID), performance, testing, and...
Use when user mentions reviewing PRs, provides GitHub PR URLs/numbers, or discusses code review. Provides structured analysis of code quality, backward compatibility, security issues, test coverage, and unaddre...
Ensure code quality or perform code reviews through comprehensive checklists and standards enforcement.
Submit code review requests to multiple AI providers (GitHub Copilot, Anthropic Claude, OpenAI Codex, Google Gemini) and get patches back. Use when user says "code review", "review this code", "get a patch for"...
Perform thorough code reviews on pull requests, diffs, or code changes. Use when asked to review code, check a PR, or provide feedback on changes.
Analyze code quality, detect code smells, identify bugs, and provide improvement recommendations. Use when reviewing code, checking quality, analyzing complexity, or when user mentions code review, refactoring...
List PRs awaiting your review, checkout the branch, run linter, and generate a structured code review document.
Code review skill. Use when reviewing changes, commits, branches, or pull requests. Focuses on bugs, structure, performance with actionable feedback.
Deep, excruciating code review. Use anytime to analyze code for correctness, edge cases, security, performance, and design issues. Not tied to baseline—this is pure code analysis.
Performs structured code reviews focusing on bugs, security, performance, and best practices. Use when reviewing code, pull requests, diffs, or when the user asks for feedback on implementations.
Performs comprehensive code review with stack detection, deep logic tracing, and double-verification of bugs before reporting
Code review framework and criteria. References security-sentinel for security checks. Use when performing code reviews or defining review standards.
Request and process code reviews with proper context. Use after completing significant implementation work.
Comprehensive code review methodology. 4 layers (Correctness, Security, Performance, Style), severity classification, 80% confidence threshold.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.