Total 50,394 skills, Code Quality has 2287 skills
Showing 12 of 2287 skills
Guide for continuous improvement, error proofing, and standardization. Use this skill when the user wants to improve code quality, refactor, or discuss process improvements.
Structure Python so LLMs can understand it in 50 lines.
AI-powered code review using CodeRabbit. Default code-review skill. Trigger for any explicit review request AND autonomously when the agent thinks a review is needed (code/PR/quality/security).
Master ShellCheck static analysis configuration and usage for shell script quality. Use when setting up linting infrastructure, fixing code issues, or ensuring script portability.
Remove AI-generated code slop from the current branch. Use after writing code to clean up unnecessary comments, defensive checks, and inconsistent style.
Run Semgrep static analysis for fast security scanning and pattern matching. Use when asked to scan code with Semgrep, write custom YAML rules, find vulnerabilities quickly, use taint mode, or set up Semgrep in CI/CD pipelines.
Universal coding standards, best practices, and patterns for TypeScript, JavaScript, React, and Node.js development.
Runs external LLM code reviews (OpenAI Codex or Google Gemini CLI) on uncommitted changes, branch diffs, or specific commits. Use when the user asks for a second opinion, external review, codex review, gemini review, or mentions /second-opinion.
Modernize and improve legacy codebases while maintaining functionality. Use when you need to refactor old code, reduce technical debt, modernize deprecated patterns, or improve code maintainability without breaking existing behavior.
Analyze code complexity, cyclomatic complexity, maintainability index, and code churn using metrics tools. Use when assessing code quality, identifying refactoring candidates, or monitoring technical debt.
Migrate codebase from try/catch or Promise-based error handling to better-result. Use when adopting Result types, converting thrown exceptions to typed errors, or refactoring existing error handling to railway-oriented programming.
Perform comprehensive code reviews with best practices, security checks, and constructive feedback. Use when reviewing pull requests, analyzing code quality, checking for security vulnerabilities, or providing code improvement suggestions.