Agent skill · software engineering · aiskillstore
docker-workflow
Comprehensive Docker containerization workflow covering multi-stage builds, docker-compose orchestration, image optimization, debugging, and production best practices. Use when containerizing applications, setting up development environments, or deploying with Docker.
Why this skill is useful
Adds comprehensive Docker workflows, multi-stage build examples, and production best practices that enhance the AI's capabilities in containerization.
What it needs
Requires docker installed locally. About 5k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Docker Workflow (source: AutumnsGrove) Overview Docker containerization streamlines development, testing, and deployment by packaging applications with their dependencies into portable, reproducible containers. This skill guides you through professional Docker workflows from development to production. Core Capabilities Multi-stage builds: Separate build and runtime dependencies for optimal image size Docker Compose orchestration: Manage multi-container applications with networking and dependencies Image optimization: Reduce image size by 50-90% through best practices Development workflows: Hot-reload, volume mounting, and environment-specific configs Debugging tools: Container inspection, health checks, and troubleshooting utilities Production readiness: Security hardening, health checks, and deployment strategies When to Use This Skill Activate when: Containerizing a new application Setting up development environments with Docker Creating production-ready Docker images Orchestrating multi-container applications Debugging container issues Optimizing Docker builds and images Workflow Phases Phase 1: Initial Setup Create .dockerignore Exclude unnecessary files from build context: See examples/.dockerignore for comprehensive template. Key principles: Exclude build artifacts and dependencies Exclude sensitive files (.env, credentials) Exclude version control (.git) Smaller context = faster builds Analyze Application Requirements Determine: Runtime (Node.js, Python, Go, Java) Dependencies and package managers Build vs. runtime requirements Port exposure and volume needs Phase 2: Multi-Stage Dockerfile Choose Strategy Multi-stage builds reduce final image size by 50-90%: See examples/Dockerfile.multi-stage for templates for Node.js, Python, Go, Java, and Rust. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/docker-workflow--fc3b5e