docker-expert

Containerize applications with multi-stage Dockerfiles and Docker Compose workflows.

12|41|Updated Feb 5, 2026
One-click install
npx skills add https://github.com/pingwu/solo-unicorn --skill docker-expert-pingwu
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: docker-expert
Source: https://github.com/pingwu/solo-unicorn/tree/main/skills/docker-expert
Command: npx skills add https://github.com/pingwu/solo-unicorn --skill docker-expert-pingwu

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Docker workflows and containerization are often error-prone and repetitive. This skill consolidates best practices to containerize applications quickly and reliably.

Core Features & Use Cases

  • Containerize multi-language apps with optimized images and non-root execution
  • Create reproducible development and production environments with docker-compose and multi-stage builds
  • Diagnose and fix container startup issues, security hardening, and performance optimizations

Quick Start

Compose an end-to-end containerized stack by writing a multi-stage Dockerfile, a docker-compose.yml, and a .dockerignore, then run with docker-compose up.

Frequently Asked Questions about docker-expert

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write a multi-stage Dockerfile to optimize image size and secure containers?

A multi-stage Dockerfile separates the build environment from the final production image to ensure reproducible builds and secure containers. This approach minimizes image size by copying only necessary artifacts and applying non-root execution for security hardening.

What is the best way to containerize a full application stack with docker-compose?

Containerize a full stack by defining a multi-stage Dockerfile, a docker-compose.yml for service orchestration, and a .dockerignore to exclude unnecessary files. Run docker-compose up to establish reproducible development and production environments.

Does Docker work with GPU and AI workloads for containerized applications?

Docker supports GPU and AI workloads by configuring containerized applications to access underlying hardware accelerators. This skill addresses GPU configurations within Dockerfiles and docker-compose setups to ensure reproducible builds for AI processing.

Why does my containerized application fail startup, and how do I debug containers?

Debug container startup issues by diagnosing container logs, verifying layered caching structures, and implementing Dockerfile health checks. Addressing security hardening and performance optimizations also resolves common container orchestration failures in production environments.

When do I need a .dockerignore file for building Docker images?

A .dockerignore file is needed when building Docker images to exclude sensitive files and reduce build context size. Using .dockerignore ensures reproducible builds, optimizes layered caching, and prevents unnecessary files from inflating the final image.

How do I separate Dev vs Production container orchestration with Docker?

Separate Dev vs Production container orchestration by using distinct docker-compose configurations and multi-stage Dockerfiles. This workflow establishes reproducible development environments while applying security hardening and performance optimizations strictly for production containers.