Total 50,522 skills, Code Quality has 2289 skills
Showing 12 of 2289 skills
Review changes for test gaps, simplification, naming consistency, reuse opportunities, and TODO quality
Improve code readability without altering functionality using idiomatic best practices
Automate lifecycle checks for migration code (TODO(migration)). Detect expired or insufficiently documented migration code and output results in report format. It is used for checking remaining TODO(migration) entries in the codebase, cleaning up expired migration code, and taking inventory of technical debt. This is a mechanism to prevent leaving "to be deleted later" code unattended.
Validate, lint, audit, or check Makefiles and .mk files for errors.
Reduces JS/TS bundle size via unused deps, tree-shaking, code splitting with keep/discard
Coordinates code modernization: OSS replacement and bundle optimization workers
Scope-aware GitHub PR review with user-friendly tone and trust tier validation
Precise, instant code structure queries for active development — answer 'who depends on this interface before I refactor it', 'how many modules break if I change this', 'what is the real impact radius of this feature change', 'which module is the true high-coupling hotspot in this legacy codebase'. Essential before any interface change, continuous refactoring task, sprint work estimation, or when navigating unfamiliar or large legacy codebases. Requires Python 3.10+ and shell. Use nexus-mapper instead when building a full .nexus-map/ knowledge base.
Use this skill when the user asks to review a PR, do a code review, check a pull request, "review this PR", "review-pr", or "look at this pull request". Requires Gitee MCP Server to be configured.
Module and file-structure patterns for clean JavaScript architecture.
Write and audit Python code comments using antirez's 9-type taxonomy. Two modes - write (add/improve comments in code) and audit (classify and assess existing comments with structured report). Use when users request comment improvements, docstring additions, comment quality reviews, or documentation audits. Applies systematic comment classification with Python-specific mapping (docstrings, inline comments, type hints).
Deep analysis debugging mode for complex issues. Activates methodical investigation protocol with evidence gathering, hypothesis testing, and rigorous verification. Use when standard troubleshooting fails or when issues require systematic root cause analysis.