Total 30,438 skills, Code Quality has 1608 skills
Showing 12 of 1608 skills
Comprehensive Python programming guidelines based on Google's Python Style Guide. Use when you needs to write Python code, review Python code for style issues, refactor Python code, or provide Python programming guidance. Covers language rules (imports, exceptions, type annotations), style rules (naming conventions, formatting, docstrings), and best practices for clean, maintainable Python code.
Automated code review for pull requests using multiple specialized agents
Specialized skill for implementing proper error handling, logging, user-friendly error messages, and error recovery strategies. Use when implementing error handling in APIs, components, or when debugging error issues.
Review code for conceptual errors, wrong assumptions, edge cases, and overcomplication; use after medium/large changes or when risk is high.
Use this skill when validating ANY potential code review finding. Apply BEFORE classifying to verify the finding is real; can you trace incorrect behavior, is it handled elsewhere, and are you certain about framework semantics? If any answer is no, DO NOT create the finding.
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.
Code quality standards. Defines complexity management, modular design, code smell detection. Applied automatically when writing or reviewing code.
Run a strict clean-code review with a numeric score and pass/fail gate. Use when a user asks for a code review, wants Uncle Bob-style feedback, or wants unnecessary abstractions removed with SOLID/KISS discipline.
Review code changes in Tenzir projects. Use when auditing diffs or pull requests for bugs, security issues, missing tests, documentation drift, readability problems, performance regressions, user experience issues, or when deciding how to respond to GitHub review comments. Also use this skill whenever the user says "review", "look at this PR", "check my changes", "audit this diff", "what do you think of this code", or asks for feedback on any code they've written or changed — even if they don't explicitly say "code review."
Python coding standards and best practices. Applicable to code generation, code review, and code refactoring scenarios.
Review code after implementation work to identify design flaws, abstraction issues, or maintenance risks that only became clear once real code was written. Use whenever the user asks whether a recent change exposed architectural problems, whether an abstraction is fighting the implementation, or whether a refactor is justified. Be conservative and avoid suggesting refactors without concrete evidence of recurring cost or complexity.