Total 50,510 skills, Code Quality has 2287 skills
Showing 12 of 2287 skills
Use when verifying code works — after feature work, before committing, before deploy, or any request to "verify", "check", or "make sure it works"
Run quality gates on implemented feature: tests, lint, type checks, and custom validation. Use after /feature-implement completes. Use for "validate feature", "run quality gates", "check feature", or "/feature-validate". Do NOT use for ad-hoc linting or debugging.
Run Python (ruff) and JavaScript (Biome) linting, formatting, and code quality checks with auto-fix support. Use when code needs linting, formatting, or style checking before commits. Use for "lint", "format", "ruff", "biome", "code style", or "check quality". Do NOT use for comprehensive code review (use systematic-code-review).
Code quality and deviation gate between /implement and /test. Reads the task document and changed files, validates coding standards, classifies deviations (minor/medium/major), and decides whether implementation is ready for testing. Runs automatically in the auto-chain between implement and test. Also invoke manually after any implementation to catch issues before wasting a test run.
Verify a spec-driven change is complete and correctly implemented. Checks task completion, implementation evidence, and spec alignment.
Agent skill for reviewer - invoke with $agent-reviewer
Agent skill for code-analyzer - invoke with $agent-code-analyzer
Use when you need to refactor Java code to adopt modern Java features (Java 8+) — including migrating anonymous classes to lambdas, replacing Iterator loops with Stream API, adopting Optional for null safety, switching from legacy Date/Calendar to java.time, using collection factory methods, applying text blocks, var inference, or leveraging Java 25 features like flexible constructor bodies and module import declarations. Part of the skills-for-java project
Guides efficient Haskell aligned with GHC practice -- laziness and strictness, purity, fusion, newtypes, pragmas, Core reading, and space-leak avoidance. Use when writing or reviewing Haskell, optimizing or profiling, debugging strictness or memory, or when the user mentions GHC, thunks, foldl vs foldl', list fusion, SPECIALIZE, or UNPACK.
Reviews codebases, architectures, PRs, and technical plans for vanity engineering — code and systems built for the developer's ego, resume, or intellectual pleasure rather than delivering user or business value. Triggers on: "review this code", "is this over-engineered", "code review", "architecture review", "complexity audit", "vanity check", "is this necessary", "simplify this", "tech debt review", or any request to evaluate whether code or architecture is justified by actual requirements. Also trigger when the user shares a codebase and asks for feedback, when discussing framework/library choices, when reviewing PRs, or when someone is debating whether to refactor or rebuild. Nudge activation when you detect patterns of unnecessary abstraction, premature optimization, or resume-driven technology choices in code the user shares — even if they haven't asked for a vanity review.
Analyze what code will be affected by changes. Use when user asks "what will break if I change X", "impact of changing X", "dependencies of X", "is it safe to modify X", or before making significant code changes.
Review a git diff or explicit file scope for reuse, code quality, efficiency, clarity, and standards issues, then optionally apply safe Codex-driven fixes. Use when the user asks to "simplify code", "review changed code", "check for code reuse", "review code quality", "review efficiency", "simplify changes", "clean up code", "refactor changes", or "run simplify".