Total 52,250 skills, Code Quality has 2360 skills
Showing 8 of 2360 skills
This skill should be used when the user asks to "manage review skills config", "update review skills", "discover review skills", "manage review presets", "validate review config", or mentions managing code review skills configuration. Use for configuration management tasks.
Diff Review - analyzes code changes and provides structured feedback before commit
Reviews code for project standards compliance and finds duplicates. Use when - reviewing code quality, checking standards, finding duplicates, analyzing compliance. Trigger keywords - standards review, check standards, find duplicates, code review, compliance check, reusable code.
Write meaningful documentation that explains why not what; focus on complex business logic and self-documenting code
Code-reviews Pluggy API integrations against Pluggy's official documentation (queried in real time via the Pluggy MCP, with a web fallback to docs.pluggy.ai when the MCP isn't connected) and returns a diagnostic report (✅/❌/⚠️) with file, line, and the code fix for each issue. Use WHENEVER the dev uploads integration files and asks to review, analyze, diagnose, or validate their Pluggy integration — or says things like "review my integration", "check my Pluggy code", "is this ready for production?", "Pluggy Doctor", "check my webhooks", "is my integration secure?", or the Portuguese variants "analisa minha integração", "revisa meu código da Pluggy", "tá tudo certo pra ir pra produção?", "checa meus webhooks", "minha integração tá segura?". Also trigger when the dev pastes/uploads code that clearly calls the Pluggy API (connect_token, GET /items, item/created webhooks, clientUserId, etc.) and wants to know if it's correct, even without saying "Pluggy Doctor". This skill is for REVIEWING existing code, not writing an integration from scratch.
Detects entropy signals in a codebase: stale TODOs, disabled tests, lint suppressions, commented-out code, dead imports, empty catch blocks, and deprecated API usage. Designed for daily runs to catch quality erosion early. Do NOT use for feature work, refactoring planning, or security audits.
Keep cyclomatic complexity low; flatten control flow, extract helpers, and prefer table-driven/strategy patterns over large switches
Refine AI-generated code through specific feedback—point out errors, identify gaps, show desired changes, reference style guides