Automate application deployment across Docker, Kubernetes, AWS, and Vercel with CI/CD pipelines.
Works with
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
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondeployment-automationExecute the skills CLI command in your project's root directory to begin installation:
Fetches deployment-automation from supercent-io/skills-template and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate deployment-automation. Access via /deployment-automation in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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 /app/node_modules ./node_modules
COPY /app/dist ./dist
COPY /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 \
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
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
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
mMake data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
supercent-io/skills-template
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
Solid pick for teams standardizing on skills: deployment-automation is focused, and the summary matches what you get after install.
deployment-automation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
deployment-automation reduced setup friction for our internal harness; good balance of opinion and flexibility.
deployment-automation has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend deployment-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: deployment-automation is the kind of skill you can hand to a new teammate without a long onboarding doc.
deployment-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: deployment-automation is focused, and the summary matches what you get after install.
deployment-automation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
deployment-automation has been reliable in day-to-day use. Documentation quality is above average for community skills.
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