Total 54,003 skills, Code Quality has 2432 skills
Showing 12 of 2432 skills
Guidance on Python code style optimization and Pythonic idioms; Based on the complete content of *One Python Craftsman* and the "Friendly Python" concept, covering variable naming, control flow, data types, container types, function design, exception handling, decorators, file operations, and SOLID principles; Providing user-friendly and maintainer-friendly design patterns, review checklists, and over 140 practical templates
This skill is used when users request phrases such as 'handle PR review issues', 'fix review items', 'resolve PR feedback', 'process review issues one by one', 'complete review tasks', 'run pr review resolver', 'resolve PR review', 'address review comments', 'fix review findings', or 'handle code review'. It reads the review comments of the PR associated with the current branch, discusses each unresolved issue with the user one by one, lets the user decide on the handling approach, and executes fixes in parallel as background subtasks.
Senior engineering analyst for code review, plan review, and automation review. Four-lens review covering architecture, code quality, reliability, and performance, each scored 1-10. Delivers APPROVE, REVISE, or REJECT verdicts. Use when you need a code review, plan review, quality check, or want to verify work before shipping. Part of the architect-system loop. Reads from system/blueprints/ and source code. Outputs to system/reviews/.
Clean up code, remove dead code, and optimize project structure. Use when user wants to clean codebase, remove unused code, or optimize imports.
Analyze codebases for anti-patterns, code smells, and quality issues using ast-grep structural pattern matching. Use when reviewing code quality, identifying technical debt, or performing comprehensive code analysis across JavaScript, TypeScript, Python, Vue, React, or other supported languages.
Mutation testing to validate test quality before PR creation. Runs mutation tools, enforces 100% kill rate, reports surviving mutants with recommended fixes. Activate when validating test coverage, preparing pull requests, checking test quality, or when asked about mutation testing.
This skill composes project AGENTS.md constitution files into openspec/config.yaml to inject quality validation gates into OpenSpec workflows. Use this skill when initializing openspec for the first time in a project or when AGENTS.md files are updated. The skill ensures openspec artifacts are validated against project-specific quality criteria from constitutions.
Compiler sanitizer skill for runtime bug detection in C/C++. Use when enabling and interpreting AddressSanitizer (ASan), UndefinedBehaviorSanitizer (UBSan), ThreadSanitizer (TSan), MemorySanitizer (MSan), or LeakSanitizer (LSan) with GCC or Clang. Activates on queries about sanitizer flags, sanitizer reports, ASAN_OPTIONS, memory errors, data races, undefined behaviour, uninitialised reads, or choosing which sanitizer to use for a given bug class.
Deep code audit that finds dead wiring, silent failures, unfinished features, placeholder stubs, bloated files, and unnecessary complexity. Produces an actionable report with file:line references grouped by severity. Think of it as a senior dev doing a thorough PR review of the entire codebase. Triggers on: "code review", "audit the code", "review the code", "find dead code", "find placeholders", "check for stubs", "prune the code", "code cleanup", "implementation review", "completeness check", "find unused code".
Run comprehensive PR checks including reviewing CodeRabbit comments, ensuring PR description quality, running pre-commit hooks, tests, and validation. Use on an existing PR to address review feedback.
This skill guides writing of new Ruby code following modern Ruby 3.x syntax, Sandi Metz's 4 Rules for Developers, and idiomatic Ruby best practices. Use when creating new Ruby files, writing Ruby methods, or refactoring Ruby code to ensure adherence to clarity, simplicity, and maintainability standards.
Comprehensive code reviewer for Java and Python implementations focusing on correctness, efficiency, code quality, and algorithmic optimization. Reviews LeetCode solutions, data structures, and algorithm implementations. Use when reviewing code, checking solutions, or providing feedback on implementations.