Loading...
Loading...
Found 1,266 Skills
Quality verification before commits and deployments. Use for quality checks, running tests, checking coverage, validating changes.
Enforces minimum quality thresholds in CI including code coverage, linting, type checking, and security scanning. Provides required checks, PR rules, and automated enforcement. Use for "quality gates", "CI checks", "code quality", or "PR requirements".
Use when preparing branches, commits, or PRs for Python changes — scoping work, running validation gates, and ensuring merge readiness. Also use when debugging CI gate failures, resolving lockfile conflicts, or uncertain what checks to run before opening a PR.
Systematic debugging that identifies root causes rather than treating symptoms. Uses sequential thinking for complex analysis, web search for research, and structured investigation to avoid circular reasoning and whack-a-mole fixes.
This skill guides systematic code refactoring following the DRY (Don't Repeat Yourself) principle. Use it when users request to eliminate code duplication, refactor repetitive code, apply the DRY principle, or mention code smells like copy-paste code, magic numbers, or repeated logic. It implements a 4-step workflow from identifying repetition to verified refactoring.
KISS, DRY, YAGNI principles for simple, maintainable code
Systematic 4-phase debugging with root cause investigation. Use when fixing bugs to prevent random fixes.
Test-Driven Development with Iron Laws enforcement. Use when writing any production code to ensure tests are written first. Includes testing-expert capabilities.
Improve code quality, reduce technical debt, restructure for maintainability
Expertise in Go programming according to the Google Go Best Practices. Focuses on actionable advice for naming, error handling, performance, testing, and general idiomatic Go to ensure high-quality, maintainable, and efficient codebases.
Use when applying Biome's linting capabilities, rule categories, and code quality enforcement to JavaScript/TypeScript projects.
Automated code review with security, performance, and best practices analysis. Use when reviewing pull requests or analyzing code for vulnerabilities, performance issues, or maintainability concerns.