deployment-automation

supercent-io/skills-template · updated Apr 8, 2026

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$npx skills add https://github.com/supercent-io/skills-template --skill deployment-automation
0 commentsdiscussion
summary

Automate application deployment across Docker, Kubernetes, AWS, and Vercel with CI/CD pipelines.

  • Covers Docker containerization with multi-stage builds, GitHub Actions workflows for testing and image building, and Kubernetes deployment with rolling updates and autoscaling
  • Includes zero-downtime deployment strategies using blue-green deployments and health check validation
  • Provides configuration templates for Vercel/Netlify frontend deployments, environment variable management, and gr
skill.md

Deployment Automation

When to use this skill

  • New Projects: Set up automated deployment from scratch
  • Manual Deployment Improvement: Automate repetitive manual tasks
  • Multi-Environment: Separate dev, staging, and production environments
  • Scaling: Introduce Kubernetes to handle traffic growth

Instructions

Step 1: Docker Containerization

Package the application as a Docker image.

Dockerfile (Node.js app):

# Multi-stage build for smaller image size
FROM node:18-alpine AS builder

WORKDIR /app

# Copy package files and install dependencies
COPY package*.json ./
RUN npm ci --only=production

# Copy source code
COPY . .

# Build application (if needed)
RUN npm run build

# Production stage
FROM node:18-alpine

WORKDIR /app

# Copy only necessary files from builder
COPY --from=builder /app/node_modules ./node_modules
COPY --from=builder /app/dist ./dist
COPY --from=builder /app/package.json ./

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

# Expose port
EXPOSE 3000

# Health check
HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
  CMD node healthcheck.js

# Start application
CMD ["node", "dist/index.js"]

.dockerignore:

node_modules
npm-debug.log
.git
.env
.env.local
dist
build
coverage
.DS_Store

Build and Run:

# Build image
docker build -t myapp:latest .

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

# Check logs
docker logs myapp-container

# Stop and remove
docker stop myapp-container
docker rm myapp-container

Step 2: GitHub Actions CI/CD

Automatically runs tests and deploys on code push.

.github/workflows/deploy.yml:

name: CI/CD Pipeline

on:
  push:
    branches: [main, develop]
  pull_request:
    branches: [main]

env:
  NODE_VERSION: '18'
  REGISTRY: ghcr.io
  IMAGE_NAME: ${{ github.repository }}

jobs:
  test:
    runs-on: ubuntu-latest

    steps:
      - uses: actions/checkout@v4

      - name: Setup Node.js
        uses: actions/setup-node@v4
        with:
          node-version: ${{ env.NODE_VERSION }}
          cache: 'npm'

      - name: Install dependencies
        run: npm ci

      - name: Run linter
        run: npm run lint

      - name: Run tests
        run: npm test -- --coverage

      - name: Upload coverage
        uses: codecov/codecov-action@v3
        with:
          files: ./coverage/coverage-final.json

  build:
    needs: test
    runs-on: ubuntu-latest
    if: github.event_name == 'push' && github.ref == 'refs/heads/main'

    steps:
      - uses: actions/checkout@v4

      - name: Set up Docker Buildx
        uses: docker/setup-buildx-action@v3

      - name: Log in to Container Registry
        uses: docker/login-action@v3
        with:
          registry: ${{ env.REGISTRY }}
          username: ${{ github.actor }}
          password: ${{ secrets.GITHUB_TOKEN }}

      - name: Extract metadata
        id: meta
        uses: docker/metadata-action@v5
        with:
          images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
          tags: |
            type=sha,prefix={{branch}}-
            type=semver,pattern={{version}}
            latest

      - name: Build and push Docker image
        uses: docker/build-push-action@v5
        with:
          context: .
          push: true
          tags: ${{ steps.meta.outputs.tags }}
          labels: ${{ steps.meta.outputs.labels }}
          cache-from: type=gha
          cache-to: type=gha,mode=max

  deploy:
    needs: build
    runs-on: ubuntu-latest
    environment: production

    steps:
      - name: Deploy to production
        uses: appleboy/ssh-[email protected]
        with:
          host: ${{ secrets.PROD_HOST }}
          username: ${{ secrets.PROD_USER }}
          key: ${{ secrets.PROD_SSH_KEY }}
          script: |
            cd /app
            docker pull ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:latest
            docker-compose up -d --no-deps --build web
            docker image prune -f

Step 3: Kubernetes Deployment

Implement scalable container orchestration.

k8s/deployment.yaml:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
  namespace: production
  labels:
    app: myapp
spec:
  replicas: 3
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      m
how to use deployment-automation

How to use deployment-automation 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 deployment-automation
2

Execute installation command

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

$npx skills add https://github.com/supercent-io/skills-template --skill deployment-automation

The skills CLI fetches deployment-automation from GitHub repository supercent-io/skills-template 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/deployment-automation

Reload or restart Cursor to activate deployment-automation. Access the skill through slash commands (e.g., /deployment-automation) 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

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

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

Ratings

4.640 reviews
  • Omar Verma· Dec 20, 2024

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

  • Arya Zhang· Dec 4, 2024

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

  • Charlotte Desai· Nov 23, 2024

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

  • Soo Haddad· Nov 11, 2024

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

  • Kabir Desai· Oct 14, 2024

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

  • Advait Khan· Oct 2, 2024

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

  • Piyush G· Sep 25, 2024

    deployment-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Soo Malhotra· Sep 21, 2024

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

  • Advait Martinez· Sep 9, 2024

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

  • Soo Khan· Sep 9, 2024

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

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