Total 50,402 skills, Code Quality has 2287 skills
Showing 12 of 2287 skills
Track, categorize, and prioritize technical debt across the codebase. Scans for debt indicators, maintains a debt register, and recommends repayment scheduling.
Structured performance profiling workflow. Identifies bottlenecks, measures against budgets, and generates optimization recommendations with priority rankings.
Request coding agents to review code, verify review results and fix confirmed issues
Performance and scalability analysis specialist. Identifies algorithmic inefficiencies, N+1 queries, memory leaks, and concurrency issues. Use when reviewing loops, database queries, file I/O, or high-concurrency code.
Triage and orchestrate code reviews. Analyzes PR intent, identifies touched surfaces, assesses risk, and routes to specialist skills. Does NOT perform detailed review - delegates to specialists. Supports full pipeline with "Review PR <number>" command.
Apply when designing types, reviewing a function signature, or writing code in any statically-typed language. Make illegal states unrepresentable, brand semantic primitives, parse external data at boundaries, refuse to lie to the compiler, exhaust variants, derive from authoritative schemas.
Provides comprehensive code review covering 6 focused aspects - architecture & design, code quality, security & dependencies, performance & scalability, testing coverage, and documentation & API design. Use this skill for deep analysis with actionable feedback after significant code changes.
Spawn a focused code review subagent. Use after every RED/GREEN cycle (pass the files changed in that cycle), after a commit, or whenever the user asks for a review. Always use this skill for reviews — it ensures the review lens is test-first and findings are fix-oriented.
Use when preparing a pull request for merge: inspect diffs, collect checks and review comments, classify findings, fix safe issues, verify, and loop until merge-ready.
Verify code against paper. Use when user asks "does this match the paper", "check my implementation", or is implementing equations/algorithms from literature.
Review pull requests for code quality, security issues, and best practices. Use when reviewing PRs, checking code changes, or analyzing diffs before merge.
Reviews Python code for type safety, async patterns, error handling, and common mistakes. Use when reviewing .py files, checking type hints, async/await usage, or exception handling.