default-workflow
Development workflow for features, bugs, refactoring. Auto-activates for multi-file implementations.
Discover Content & media skills, compare source repositories and read the instructions for each workflow.
Development workflow for features, bugs, refactoring. Auto-activates for multi-file implementations.
Test strategy, execution, and coverage analysis. Use when designing tests, running test suites, or analyzing test results beyond baseline checks.
Dispatch code-reviewer subagent to review implementation against plan or requirements before proceeding
Docker image reviews, optimization, and step-building guidance. Analyzes Dockerfiles for best practices, security issues, and anti-patterns.
Production Kubernetes platform patterns covering cluster architecture, security, GitOps, observability, autoscaling, and operational guardrails
Single source of truth for repository structure and entry points, including key directories, domain boundaries, shared code, integrations, and build/deploy references
Practical deployment strategies (rolling, blue-green, canary) for safe releases with rollback, health checks, and database compatibility guidance—without requiring full Kubernetes complexity
Comprehensive guide for ML model versioning and management strategies, including model registries, metadata tracking, and deployment workflows.
Language-aware build orchestration that detects project language and runs appropriate build pipeline
Infrastructure as Code for IoT environments using Terraform, Ansible, and GitOps for scalable, reproducible infrastructure
Implement Software/Model Bill of Materials (SBOM/MBOM) for AI systems, vulnerability management, adversarial attack defense, and trusted AI pipelines to secure the AI supply chain from training to deployment.
Gradually rolling out new versions to a subset of users, monitoring for issues, and expanding the rollout if everything looks healthy to minimize risk and enable fast rollback.
Review architecture compliance before execution
Comprehensive guide to regression benchmarks for AI systems including test suite creation, CI/CD integration, and continuous benchmarking strategies
This skill should be used when the user asks to "run ralph", "set up ralph", "create a PRD workflow", "use ralph-orchestrator", "autonomous coding loop", "hat-based agents", or mentions ralph tasks, ralph prese...
Patterns for distributing configuration and secrets to services safely and consistently across environments (env vars, config files, secret managers, K8s External Secrets, and change process)
Centralized repository for managing ML model lifecycle, versions, artifacts, and deployment metadata at enterprise scale
Platform/Language agnostic API delivery and correctness auditor. Use when project contains API endpoints to verify contract alignment, endpoint behavior, and test coverage.
Create .agent/baseline.md and later compare against it. Use when capturing baseline build/lint/test results or investigating newly introduced findings.
Performs systematic code review checking for correctness, maintainability, security, and best practices. Activates when user requests review, before creating PRs, or when significant code changes are ready. Ens...
Conventions for service configuration and environment variables: naming, precedence, validation at startup, secrets handling, environment detection, and documentation patterns
Use when working with Docker containers, creating Dockerfile configurations, writing docker-compose files, setting up CI/CD pipelines with GitHub Actions, or managing infrastructure deployments.
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Checklist gate สำหรับ production release ครอบคลุม testing, documentation, rollback plan, และ stakeholder sign-off
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.