Total 54,186 skills, Code Quality has 2444 skills
Showing 12 of 2444 skills
Code refactoring patterns and techniques for improving code quality without changing behavior. Use for cleaning up legacy code, reducing complexity, or improving maintainability.
CRITICAL: Use for unsafe Rust code review and FFI. Triggers on: unsafe, raw pointer, FFI, extern, transmute, *mut, *const, union, #[repr(C)], libc, std::ffi, MaybeUninit, NonNull, SAFETY comment, soundness, undefined behavior, UB, safe wrapper, memory layout, bindgen, cbindgen, CString, CStr, 安全抽象, 裸指针, 外部函数接口, 内存布局, 不安全代码, FFI 绑定, 未定义行为
Systematic debugging frameworks for finding and fixing bugs - includes root cause analysis, defense-in-depth validation, and verification protocols
Apply appropriate design patterns (Singleton, Factory, Observer, Strategy, etc.) to solve architectural problems. Use when refactoring code architecture, implementing extensible systems, or following SOLID principles.
Profile CPU usage to identify hot spots and bottlenecks. Optimize code paths consuming most CPU time for better performance and resource efficiency.
Codemod (JSSG, ast-grep, workflows) best practices for writing efficient, safe, and maintainable code transformations. This skill should be used when writing, reviewing, or debugging codemods, AST transformations, or automated refactoring tools. Triggers on tasks involving codemod, ast-grep, JSSG, code transformation, or automated migration.
Apply the K.I.S.S principle (Keep It Simple, Stupid) to reduce complexity, improve maintainability, and solve problems elegantly. Use when designing systems, writing code, planning solutions, creating documentation, architecting features, or making decisions where simplicity drives quality and efficiency.
Systematically trace bugs backward through call stack to find original trigger. Use when errors occur deep in execution and you need to trace back to find the original trigger.
Meta-cognitive reasoning specialist for evidence-based analysis, hypothesis testing, and cognitive failure prevention. Use when conducting reviews, making assessments, debugging complex issues, or any task requiring rigorous analytical reasoning. Prevents premature conclusions, assumption-based errors, and pattern matching without verification.
Provides refactoring recommendations and step-by-step improvement plans. Use when planning refactoring, improving code structure, or reducing technical debt.
Technical solution evaluation and code review in the style of Linus Torvalds. Only use this when the user explicitly requests a Linus-style review or explicitly asks for a rigorous evaluation of code changes/technical solutions (e.g., "review changes/code", "evaluate if the solution is appropriate", "check submission standards", "linus-tech-review").
Invoke IMMEDIATELY via python script when user requests codebase understanding, architecture comprehension, or repository orientation. Do NOT explore first - the script orchestrates exploration.