Total 50,368 skills, Code Quality has 2287 skills
Showing 12 of 2287 skills
CRITICAL: Use for performance optimization. Triggers: performance, optimization, benchmark, profiling, flamegraph, criterion, slow, fast, allocation, cache, SIMD, make it faster, 性能优化, 基准测试
This skill should be used when the user asks to "simplify code", "clean up code", "refactor for clarity", "reduce complexity", "improve readability", "make this easier to maintain", or asks to simplify recently modified code.
CRITICAL: Use for type-driven design. Triggers: type state, PhantomData, newtype, marker trait, builder pattern, make invalid states unrepresentable, compile-time validation, sealed trait, ZST, 类型状态, 新类型模式, 类型驱动设计
Review code for logging patterns and suggest evlog adoption. Detects console.log spam, unstructured errors, and missing context. Guides wide event design, structured error handling, request-scoped logging, and log draining with adapters (Axiom, OTLP).
PR quality checklist for ensuring comprehensive, well-documented pull requests. Use before submitting PRs to improve review efficiency and code quality.
Write clear, plain-spoken code comments and documentation that lives alongside the code. Use when writing or reviewing code that needs inline documentation—file headers, function docs, architectural decisions, or explanatory comments. Optimized for both human readers and AI coding assistants who benefit from co-located context.
Idiomatic Python 3.14+ development. Use when writing Python code, CLI tools, scripts, or services. Emphasizes stdlib, type hints, uv/ruff toolchain, and minimal dependencies.
MANDATORY for code review - must use Codex CLI for all code reviews, then apply fixes based on Codex feedback. Also use for cross-verification, debugging, and getting alternative implementations.
Provides Python patterns for type-first development with dataclasses, discriminated unions, NewType, and Protocol. Must use when reading or writing Python files.
Mandatory code reviews via /code-review before commits and deploys
Assess, quantify, and prioritize technical debt using code analysis, metrics, and impact analysis. Use when planning refactoring, evaluating codebases, or making architectural decisions.
Find function callees with GrepAI trace. Use this skill to discover what functions a specific function calls.