Total 43,685 skills, Code Quality has 2036 skills
Showing 12 of 2036 skills
Workflow for identifying and fixing static analysis errors. Use this after modifying code or if `dart analyze` fails.
Full debugging workflow — reproduce the bug with a failing test, perform root cause analysis, then implement a minimal fix.
Implement the requested changes. Write production-ready code, follow existing patterns, and run tests to verify your work.
Analyze git diffs for risk scoring, reviewer recommendations, and change classification
Scan codebases for technical debt, score severity, track trends, and generate prioritized remediation plans. Use when users mention tech debt, code quality, refactoring priority, debt scoring, cleanup sprints, or code health assessment. Also use for legacy code modernization planning and maintenance cost estimation.
Validate domain boundaries -- detect cross-context import violations and aggregate invariant issues
Optional, modular cleanups and style improvements to apply on new mo:core projects (or after mo:core migration). Covers import ordering, unused import cleanup, and single‑expression return removal, with detection checks and automation recipes.
Identificación de cuellos de botella: CPU, memoria, event loop, queries lentas, Core Web Vitals.
Scan and analyze a software repository or project for design quality using principles from A Philosophy of Software Design by John Ousterhout. Use when user asks to review, audit, scan, or evaluate code quality, design quality, architecture, or technical debt. Also trigger for: code review, design review, complexity analysis, code health check, module depth analysis, information hiding review, how good is my code, review my project, find design problems, what is wrong with my codebase, rate my code, or anything about evaluating software design quality at a structural level. This is not a linter or style checker. It evaluates deep design qualities like module depth, abstraction quality, information hiding, and complexity patterns.
Post-implementation reality check. Run after tests pass, before declaring done. Use when completing a feature, bug fix, refactor, or integration — or when asked to verify, sanity check, or confirm something actually works.
Reviews Swift code for concurrency correctness, modern API usage, and common async/await pitfalls. Use when reading, writing, or reviewing Swift concurrency code.
Use this skill when building Python desktop applications using PySide6 with strict MVC architecture where all UI is defined by .ui files. Covers architecture patterns, controller/model/view separation, signal handling, and .ui file workflows.