Total 44,141 skills, Code Quality has 2071 skills
Showing 12 of 2071 skills
Use when conducting comprehensive code review for pull requests across multiple quality dimensions. Orchestrates 12-15 specialized reviewer agents across 4 phases using star topology coordination. Covers automated checks, parallel specialized reviews (quality, security, performance, architecture, documentation), integration analysis, and final merge recommendation in a 4-hour workflow.
Fix bug command
This skill should be used when analyzing codebases, understanding architecture, or when "analyze", "investigate", "explore code", or "understand architecture" are mentioned.
Refines code changes for better reviewability. Validates change cohesion (no mixed concerns), generates clear commit messages, creates PR/MR with reviewer-focused descriptions. Use when committing, reviewing, creating PR/MR, or mentions "commit", "review", "PR", "MR", "pull request", "merge request", "refine", "提交", "审查".
Python 开发规范，包含 PEP 8 风格、类型注解、异常处理、测试规范等
Enforce 2026 folder structure standards - feature-based organization, max nesting depth, unidirectional imports. Blocks structural violations. Use when creating files or reviewing project architecture.
Conduct Pull Request code reviews, including comprehensive evaluations of code quality, security, performance, architectural rationality, etc. Activated when users request PR reviews or mention keywords like "review pr", "check PR", etc.
Audit code for DRY violations, dead code, complexity, and consistency issues. Read-only analysis with actionable recommendations. Use before PR or for code quality review. Triggers: review maintainability, code quality, DRY, refactor review.
Audit code for over-engineering, premature optimization, and cognitive complexity. Identifies unnecessary abstractions, YAGNI violations, and overly complex solutions. Read-only analysis. Triggers: review simplicity, over-engineering, complexity check, YAGNI.
Systematic methodology for debugging bugs, test failures, and unexpected behavior. Use when encountering any technical issue before proposing fixes. Covers root cause investigation, pattern analysis, hypothesis testing, and fix implementation. Use ESPECIALLY when under time pressure, "just one quick fix" seems obvious, or you've already tried multiple fixes. NOT for exploratory code reading.
This skill should be used when making design decisions, evaluating trade-offs, assessing code quality, or when "engineering judgment" or "code quality" are mentioned.
Remove AI-generated code slop from the current branch. Use when the user says "deslop" or asks to clean up AI slop, remove AI code patterns, or clean the branch before committing.