Total 30,617 skills, Code Quality has 1617 skills
Showing 12 of 1617 skills
Common Python anti-patterns to avoid. Use as a checklist when reviewing code, before finalizing implementations, or when debugging issues that might stem from known bad practices.
4-phase systematic debugging methodology with root cause analysis and evidence-based verification. Use when debugging complex issues.
Identifies and fixes component hierarchy issues by detecting orphaned classes in root namespaces and ensuring components exist only as leaf nodes. Use when analyzing component structure, finding orphaned classes, flattening component hierarchies, removing component nesting, or when the user asks about component flattening, orphaned classes, or component structure cleanup.
Manually trigger the cdd-code-simplifier agent to review and simplify code
Apply the K.I.S.S principle (Keep It Simple, Stupid) to reduce complexity, improve maintainability, and solve problems elegantly. Use when designing systems, writing code, planning solutions, creating documentation, architecting features, or making decisions where simplicity drives quality and efficiency.
Expert-level performance optimization, profiling, benchmarking, and tuning
Comprehensive dependency health auditing for JavaScript/TypeScript projects. Run npm audit, detect outdated packages, check for security advisories, and verify license compliance. Prioritises vulnerabilities by severity and provides actionable fix recommendations. Use when: auditing project dependencies, checking for vulnerabilities, updating packages, preparing for release, or investigating "npm audit" warnings. Keywords: audit, vulnerabilities, outdated, security, npm audit, pnpm audit, CVE, GHSA, license.
Run Semgrep static analysis scans and create custom detection rules. Use when asked to scan code with Semgrep, find security vulnerabilities, write custom YAML rules, or detect specific bug patterns.
Use when working with performance testing review multi agent review
Quality verification before commits and deployments. Use for quality checks, running tests, checking coverage, validating changes.
Run verification commands and confirm output before claiming success. Use when about to claim work is complete, fixed, or passing, before committing or creating PRs.
Code review practices with technical rigor and verification gates. Use for receiving feedback, requesting code-reviewer subagent reviews, or preventing false completion claims in pull requests.