testing-strategies
Test features, debug issues, run manual or automated tests, collect logs. Use when testing, debugging, validating, running tests, or analyzing errors.
Test features, debug issues, run manual or automated tests, collect logs. Use when testing, debugging, validating, running tests, or analyzing errors.
Use when you have a written implementation plan to execute. Load plan, review critically, execute tasks in batches with verification.
Quick reference for frequently performed development tasks like building, testing, and debugging
Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management
Comprehensive guide for writing shell script tests using Bats (Bash Automated Testing System). Use when writing or improving tests for Bash/shell scripts, creating test fixtures, mocking commands, or setting up CI/CD for shell script testing. Includes patterns for assertions, setup/teardown, mocking, fixtures, and integration with GitHub Actions.
Elite testing skill for creating comprehensive, production-grade test suites with meaningful coverage. Use when (1) writing new test files or test suites, (2) improving test coverage for existing code, (3) the user requests "test", "testing", "write tests", "test coverage", or "unit tests", (4) creating integration, e2e, or API tests, (5) validating code quality through testing, (6) setting up testing infrastructure, or (7) the user explicitly wants tests that catch real bugs, not just superficial coverage.
Parallelize operations across dynamic target lists using GitHub Actions matrix strategies with failure isolation, rate limiting, and conditional logic.
Autonomous task loop that picks ready tasks, implements them, updates progress.txt, commits, and repeats. Use when asked to 'build feature', 'run the loop', or 'implement these tasks'.
State-of-the-art debugging agent with hypothesis-driven analysis, automatic code instrumentation, git worktree isolation, and browser automation. Use when debugging errors, stack traces, unexpected behavior, performance issues, failed tests, race conditions, or hard-to-reproduce bugs.
Provides Git version control operations for managing code repositories. Allows agents to check repository status, view commit history, and perform basic Git operations.
Create AI-assisted code reviews on GitHub, GitLab, or Forgejo. Use when asked to review a PR/MR, analyze code changes, or provide review feedback.
Skip unnecessary CI/CD operations before execution. Detect unchanged content, cached builds, and irrelevant paths to reduce workflow costs and execution time.
CI/CD pipeline design, GitHub Actions, and deployment automation. Auto-triggers when setting up pipelines, automating deployments, or configuring workflows.
Guide proper GitOps workflow for Kubernetes changes instead of direct kubectl mutations. Identifies resources, locates/creates manifests, commits to git, and syncs via ArgoCD/Flux. Use when kubectl mutation is blocked.
Execute development tasks autonomously by reading GitHub Issues, implementing solutions, running tests, and managing the full development lifecycle until completion
GitLab CE self-hosted deployment on Kubernetes. Use when installing, configuring, upgrading, or managing GitLab instances including runners, container registry, backups, and external database integration.
Git worktree management for parallel SPEC development with isolated workspaces, automatic registration, and seamless MoAI-ADK integration
Use GitHub CLI (gh) for authenticated API operations including repo access, file fetching, PR creation, and user management. Activate this skill when implementing GitHub integrations, working with gh CLI commands, creating PR workflows, handling GitHub authentication, or building testable GitHub clients using the Protocol pattern.
Technology-agnostic version management system with Git tags as source of truth