docker-deployment

pluginagentmarketplace/custom-plugin-nodejs · updated Apr 8, 2026

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$npx skills add https://github.com/pluginagentmarketplace/custom-plugin-nodejs --skill docker-deployment
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summary

Master containerizing and deploying Node.js applications with Docker for consistent, portable deployments.

skill.md

Docker Deployment Skill

Master containerizing and deploying Node.js applications with Docker for consistent, portable deployments.

Quick Start

Dockerize Node.js app in 3 steps:

  1. Create Dockerfile - Define container image
  2. Build Image - docker build -t myapp .
  3. Run Container - docker run -p 3000:3000 myapp

Core Concepts

Basic Dockerfile

FROM node:18-alpine

WORKDIR /app

COPY package*.json ./
RUN npm ci --only=production

COPY . .

EXPOSE 3000

CMD ["node", "src/index.js"]

Multi-Stage Build (Optimized)

# Build stage
FROM node:18-alpine AS builder

WORKDIR /app

COPY package*.json ./
RUN npm ci --only=production

COPY . .

# Production stage
FROM node:18-alpine

WORKDIR /app

# Copy from builder
COPY --from=builder /app/node_modules ./node_modules
COPY --from=builder /app .

# Create non-root user
RUN addgroup -g 1001 -S nodejs && \
    adduser -S nodejs -u 1001

USER nodejs

EXPOSE 3000

HEALTHCHECK --interval=30s --timeout=3s \
  CMD node healthcheck.js || exit 1

CMD ["node", "src/index.js"]

Learning Path

Beginner (1-2 weeks)

  • ✅ Understand Docker basics
  • ✅ Create simple Dockerfile
  • ✅ Build and run containers
  • ✅ Manage volumes and networks

Intermediate (3-4 weeks)

  • ✅ Multi-stage builds
  • ✅ Docker Compose
  • ✅ Environment variables
  • ✅ Health checks

Advanced (5-6 weeks)

  • ✅ Image optimization
  • ✅ Production best practices
  • ✅ Container orchestration
  • ✅ CI/CD integration

Docker Compose

# docker-compose.yml
version: '3.8'

services:
  app:
    build: .
    ports:
      - "3000:3000"
    environment:
      - NODE_ENV=production
      - DATABASE_URL=postgresql://db:5432/myapp
      - REDIS_URL=redis://redis:6379
    depends_on:
      - db
      - redis
    restart: unless-stopped

  db:
    image: postgres:15-alpine
    environment:
      - POSTGRES_USER=myapp
      - POSTGRES_PASSWORD=secret
      - POSTGRES_DB=myapp
    volumes:
      - postgres-data:/var/lib/postgresql/data

  redis:
    image: redis:7-alpine
    volumes:
      - redis-data:/data

  nginx:
    image: nginx:alpine
    ports:
      - "80:80"
    volumes:
      - ./nginx.conf:/etc/nginx/nginx.conf:ro
    depends_on:
      - app

volumes:
  postgres-data:
  redis-data:

Docker Compose Commands

# Start services
docker-compose up -d

# View logs
docker-compose logs -f app

# Stop services
docker-compose down

# Rebuild images
docker-compose up -d --build

# Scale services
docker-compose up -d --scale app=3

.dockerignore

node_modules
npm-debug.log
.git
.gitignore
.env
.env.local
.vscode
*.md
tests
coverage
.github
Dockerfile
docker-compose.yml

Docker Commands

# Build image
docker build -t myapp:latest .

# Run container
docker run -d -p 3000:3000 --name myapp myapp:latest

# View logs
docker logs -f myapp

# Enter container
docker exec -it myapp sh

# Stop container
docker stop myapp

# Remove container
docker rm myapp

# List images
docker images

# Remove image
docker rmi myapp:latest

# Prune unused resources
docker system prune -a

Environment Variables

# In Dockerfile
ENV NODE_ENV=production
ENV PORT=3000

# Or in docker-compose.yml
environment:
  - NODE_ENV=production
  - PORT=3000

# Or from .env file
env_file:
  - .env.production

Volumes for Persistence

services:
  app:
    volumes:
      - ./logs:/app/logs              # Bind mount
      - node_modules:/app/node_modules # Named volume

volumes:
  node_modules:

Health Checks

# In Dockerfile
HEALTHCHECK --interval=30s --timeout=3s --start-period=5s \
  CMD node healthcheck.js || exit 1
// healthcheck.js
const http = require('http');

const options = {
  host: 'localhost',
  port: 3000,
  path: '/health',
  timeout: 2000
};

const request = http.request(options, (res) => {
  console.log(`STATUS: ${res.statusCode}`);
  process.exit(res.statusCode === 200 ? 0 : 1);
});

request.on('error', (err) => {
  console.log('ERROR:', err);
  process.exit(1);
});

request.end()
how to use docker-deployment

How to use docker-deployment on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add docker-deployment
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/pluginagentmarketplace/custom-plugin-nodejs --skill docker-deployment

The skills CLI fetches docker-deployment from GitHub repository pluginagentmarketplace/custom-plugin-nodejs and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/docker-deployment

Reload or restart Cursor to activate docker-deployment. Access the skill through slash commands (e.g., /docker-deployment) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.731 reviews
  • Piyush G· Dec 20, 2024

    Keeps context tight: docker-deployment is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Fatima Smith· Dec 20, 2024

    Useful defaults in docker-deployment — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Michael Gonzalez· Dec 8, 2024

    We added docker-deployment from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Mei Sharma· Nov 27, 2024

    docker-deployment reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Dhruvi Jain· Nov 11, 2024

    docker-deployment has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ishan Huang· Oct 18, 2024

    Registry listing for docker-deployment matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Rahul Santra· Oct 2, 2024

    Solid pick for teams standardizing on skills: docker-deployment is focused, and the summary matches what you get after install.

  • Ganesh Mohane· Sep 21, 2024

    We added docker-deployment from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Shikha Mishra· Sep 17, 2024

    I recommend docker-deployment for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Camila Dixit· Sep 17, 2024

    docker-deployment is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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