repo-analyzer
Analyze GitHub repositories for structure, documentation, dependencies, and contribution patterns. Use for codebase understanding and health assessment.
Discover Testing & security skills, compare source repositories and read the instructions for each workflow.
Analyze GitHub repositories for structure, documentation, dependencies, and contribution patterns. Use for codebase understanding and health assessment.
Rapid incident classification, severity assessment, and response coordination. Use when relevant to the task.
Gather and analyze competitive intelligence from multiple sources. Use when relevant to the task.
Merge multiple documentation sources (docs, GitHub, PDF) with conflict detection. Use when combining docs + code for complete skill coverage.
Detect requests for iterative AI task loops and invoke the Ralph command
Verify bidirectional traceability from requirements to code to tests. Use when relevant to the task.
Detects AI-generated writing patterns and suggests authentic alternatives. Auto-applies when reviewing content, editing documents, generating text, or when user mentions writing quality, AI detection, authentic...
Detect orphaned tests, obsolete assertions, and test-code misalignment. Use for test suite maintenance, cleanup, and traceability validation.
Package skills into uploadable ZIP files for Claude. Use after skill-builder/skill-enhancer to create final upload package. Use when relevant to the task.
Validate AIWG configuration files and project setup for correctness and completeness. Use when relevant to the task.
Multi-stage quality assurance protocol for marketing assets with channel-specific validation. Use when relevant to the task.
Configure TDD enforcement via pre-commit hooks and CI coverage gates. Use when setting up test-first development workflow, adding coverage gates, or enforcing TDD practices.
Analyze test coverage, identify gaps, and recommend test improvements. Use when relevant to the task.
Route natural language requests to appropriate skills and workflows. Use when relevant to the task.
Auto-generate test data factories from schemas, types, or models. Use when creating test data infrastructure, setting up fixtures, or reducing test setup boilerplate.
Split large documentation (10K+ pages) into focused sub-skills with intelligent routing. Use for massive doc sites like Godot, AWS, or MSDN.
Detect orphaned tests, obsolete assertions, and test-code misalignment. Use for test suite maintenance, cleanup, and traceability validation. Use when relevant to the task.
Check code style compliance. Use when asked to validate code style, check naming conventions, review comments quality, or ensure file naming follows conventions. Works on whole codebase or specific changes (bra...
Validate code for KISS and DRY principles. Use when asked to check for simplification opportunities, reduce duplication, review code complexity, or ensure maintainability. Works on whole codebase or specific ch...
Guidelines for pull requests descriptions. Use when asked to create a PR, or decided to create one by yourself, or when asked to write/improve PR description.
Dispatch a release using GitHub Actions. Use when asked to create a release, publish to npm, or start the release process.
Update Storybook visual regression snapshots after intentional UI changes. Use when visual tests fail due to expected changes, or when asked to update snapshots.
Update an existing pull request with new changes or respond to review feedback. Use when addressing PR comments, making requested changes, or updating a PR after review.
Run full validation to ensure code is ready for merge. Use before merging PRs, when asked to validate readiness, or as a final check before requesting review.
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.