review-code
Review code changes for quality, security, and adherence to project conventions. Use after making code changes or when reviewing a pull request.
Browse published AI skills maintained by yu-iskw. Compare skill descriptions and follow each source repository for setup instructions.
Indexed skills
10Repository stars across indexed skills
11Repository forks
4Average repository stars per indexed skill
1Repository stars may repeat across skills from the same repository.
Review code changes for quality, security, and adherence to project conventions. Use after making code changes or when reviewing a pull request.
Workflow for auditing security vulnerabilities using Trunk (Trivy and OSV-scanner). Use when checking for project vulnerabilities, hard-coded secrets, or repairing security flaws.
Build the project and automatically fix any build errors, compilation failures, or type mismatches. Use when the project fails to build, shows "broken" states, or after making significant changes.
Run linters and fix violations, formatting errors, or style mismatches using Trunk. Use when code quality checks fail, before submitting PRs, or to repair "broken" linting states.
Run unit tests and automatically fix code failures, regression bugs, or test mismatches. Use when tests are failing, after implementing new features, or to repair "broken" tests.
Set up the development environment for the project. Use when starting work on the project, when dependencies are out of sync, or to fix environment setup failures.
Step-by-step workflow for safely upgrading Go dependencies using the standard Go toolchain.
Implement Agent Skills for the user's project. Identifies the AI coding tool (Cursor, Claude Code, Gemini CLI) to ensure compatibility and provides specialized templates.
Update README.md to reflect changes in project structure, skills, and agents. Use when new components are added or architecture changes.
Central meta-skill for creating and unifying all Agent Skills. Orchestrates specialized meta-skills for analysis, workflows, tools, and scaffolding.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.