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aAAaqwq/AGI-Super-Team/skills/deployment-automation/SKILL.md

deployment-automation

Automate application deployment to cloud platforms and servers. Use when setting up CI/CD pipelines, deploying to Docker/Kubernetes, or configuring cloud infrastructure. Handles GitHub Actions, Docker, Kubernetes, AWS, Vercel, and deployment best practices.

Source repository stars
89
Declared platforms
0
Static risk flags
2
Last source update
2026-08-26
Source checked
2026-08-28

Decision brief

What it does: where it fits

Automate application deployment to cloud platforms and servers. Handles GitHub Actions, Docker, Kubernetes, AWS, Vercel, and deployment best practices.

Best for

  • New Projects: Set up automated deployment from scratch
  • Manual Deployment Improvement: Automate repetitive manual tasks
  • Multi-Environment: Separate dev, staging, and production environments

Not for

  • Tasks that require unconfirmed production actions or broad system permissions.
  • Environments where the pinned source and install steps cannot be inspected.

Compatibility matrix

Platform support, with evidence labels

PlatformStatusEvidenceWhat to check
CodexNot declaredNo explicit evidencePortability before use
Claude CodeNot declaredNo explicit evidencePortability before use
CursorNot declaredNo explicit evidencePortability before use
Gemini CLINot declaredNo explicit evidencePortability before use
Open the compatibility checker

Installation

Inspect first. Install second.

The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

Source-detected install commandSource
npx skills add https://github.com/aAAaqwq/AGI-Super-Team --skill "skills/deployment-automation"
Safe inspection promptEditorial

Inspect the Agent Skill "deployment-automation" from https://github.com/aAAaqwq/AGI-Super-Team/blob/bfcfb64081f94e5869ff420aaaed63b6da716bc6/skills/deployment-automation/SKILL.md at commit bfcfb64081f94e5869ff420aaaed63b6da716bc6. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

Workflow

What the source asks the agent to do

  1. 01

    Instructions

    Package the application as a Docker image.

    Package the application as a Docker image.Dockerfile (Node.js app): dockerfile
  2. 02

    Step 1: Docker Containerization

    Package the application as a Docker image.

    Package the application as a Docker image.Dockerfile (Node.js app): dockerfile
  3. 03

    Multi-stage build for smaller image size

    FROM node:18-alpine AS builder

    FROM node:18-alpine AS builder
  4. 04

    Production stage

    Review the “Production stage” section in the pinned source before continuing.

    Review and apply the “Production stage” source section.
  5. 05

    Step 2: GitHub Actions CI/CD

    Automatically runs tests and deploys on code push.

    Automatically runs tests and deploys on code push..github/workflows/deploy.yml:

Permission review

Static risk signals and limitations

Runs scripts

medium · line 65

The documentation asks the agent to run terminal commands or scripts.

npm-debug.log

Runs scripts

medium · line 78

The documentation asks the agent to run terminal commands or scripts.

docker build -t myapp:latest .

Network access

medium · line 436

The documentation includes network, browsing, or remote request actions.

if curl -f http://localhost:8080/health; then

Evidence record

Why each signal appears

EvidenceSourceComputedTestedEditorial
SignalValueEvidence typeMeaning
Quality score95/100ComputedDocumentation, specificity, maintenance, and trust rules
Repository stars89SourceRepository attention, not individual Skill quality
Compatibility0 platformsSourceDeclared in the catalog source record
Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

Pinned source

Provenance and original SKILL.md

Repository
aAAaqwq/AGI-Super-Team
Skill path
skills/deployment-automation/SKILL.md
Commit
bfcfb64081f94e5869ff420aaaed63b6da716bc6
License
MIT
Collected
2026-08-28
Default branch
main
View the original 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/[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
      maxUnavailable: 0
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
      - name: myapp
        image: ghcr.io/username/myapp:latest
        imagePullPolicy: Always
        ports:
        - containerPort: 3000
        env:
        - name: NODE_ENV
          value: "production"
        - name: DATABASE_URL
          valueFrom:
            secretKeyRef:
              name: myapp-secrets
              key: database-url
        resources:
          requests:
            memory: "128Mi"
            cpu: "100m"
          limits:
            memory: "256Mi"
            cpu: "200m"
        livenessProbe:
          httpGet:
            path: /health
            port: 3000
          initialDelaySeconds: 30
          periodSeconds: 10
        readinessProbe:
          httpGet:
            path: /ready
            port: 3000
          initialDelaySeconds: 5
          periodSeconds: 5

---
apiVersion: v1
kind: Service
metadata:
  name: myapp-service
  namespace: production
spec:
  selector:
    app: myapp
  ports:
  - protocol: TCP
    port: 80
    targetPort: 3000
  type: LoadBalancer

---
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: myapp-hpa
  namespace: production
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: myapp
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 80

Deployment Script (deploy.sh):

#!/bin/bash
set -e

# Variables
NAMESPACE="production"
IMAGE_TAG="${1:-latest}"

echo "Deploying myapp:${IMAGE_TAG} to ${NAMESPACE}..."

# Apply Kubernetes manifests
kubectl apply -f k8s/namespace.yaml
kubectl apply -f k8s/secrets.yaml
kubectl apply -f k8s/deployment.yaml
kubectl apply -f k8s/service.yaml

# Update image
kubectl set image deployment/myapp myapp=ghcr.io/username/myapp:${IMAGE_TAG} -n ${NAMESPACE}

# Wait for rollout
kubectl rollout status deployment/myapp -n ${NAMESPACE} --timeout=5m

# Verify
kubectl get pods -n ${NAMESPACE} -l app=myapp

echo "Deployment completed successfully!"

Step 4: Vercel/Netlify (Frontend)

Simply deploy static sites and Next.js apps.

vercel.json:

{
  "version": 2,
  "builds": [
    {
      "src": "package.json",
      "use": "@vercel/next"
    }
  ],
  "env": {
    "DATABASE_URL": "@database-url",
    "API_KEY": "@api-key"
  },
  "regions": ["sin1", "icn1"],
  "headers": [
    {
      "source": "/(.*)",
      "headers": [
        {
          "key": "X-Frame-Options",
          "value": "DENY"
        },
        {
          "key": "X-Content-Type-Options",
          "value": "nosniff"
        }
      ]
    }
  ],
  "redirects": [
    {
      "source": "/old-path",
      "destination": "/new-path",
      "permanent": true
    }
  ]
}

CLI Deployment:

# Install Vercel CLI
npm i -g vercel

# Login
vercel login

# Deploy to preview
vercel

# Deploy to production
vercel --prod

# Set environment variable
vercel env add DATABASE_URL

Step 5: Zero-Downtime Deployment Strategy

Deploy new versions without service interruption.

Blue-Green Deployment (docker-compose):

version: '3.8'

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

  app-blue:
    image: myapp:blue
    environment:
      - NODE_ENV=production
      - COLOR=blue

  app-green:
    image: myapp:green
    environment:
      - NODE_ENV=production
      - COLOR=green

switch.sh (Blue/Green Switch):

#!/bin/bash

CURRENT_COLOR=$(cat current_color.txt)
NEW_COLOR=$([[ "$CURRENT_COLOR" == "blue" ]] && echo "green" || echo "blue")

# Deploy new version to inactive environment
docker-compose up -d app-${NEW_COLOR}

# Wait for health check
sleep 10

# Health check
if curl -f http://localhost:8080/health; then
  # Update nginx to point to new environment
  sed -i "s/${CURRENT_COLOR}/${NEW_COLOR}/g" nginx.conf
  docker-compose exec nginx nginx -s reload

  # Update current color
  echo ${NEW_COLOR} > current_color.txt

  # Stop old environment after 5 minutes (rollback window)
  sleep 300
  docker-compose stop app-${CURRENT_COLOR}

  echo "Deployment successful! Switched to ${NEW_COLOR}"
else
  echo "Health check failed! Keeping ${CURRENT_COLOR}"
  docker-compose stop app-${NEW_COLOR}
  exit 1
fi

Output format

Deployment Checklist

## Deployment Checklist

### Pre-Deployment
- [ ] All tests passing (unit, integration, E2E)
- [ ] Code review approved
- [ ] Environment variables configured
- [ ] Database migrations ready
- [ ] Rollback plan documented

### Deployment
- [ ] Docker image built and tagged
- [ ] Image pushed to container registry
- [ ] Kubernetes manifests applied
- [ ] Rolling update started
- [ ] Pods healthy and ready

### Post-Deployment
- [ ] Health check endpoint responding
- [ ] Metrics/logs monitoring active
- [ ] Performance baseline established
- [ ] Old pods terminated (after grace period)
- [ ] Deployment documented in changelog

Constraints

Required Rules (MUST)

  1. Health Checks: Health check endpoint for all services

    app.get('/health', (req, res) => {
      res.status(200).json({ status: 'ok' });
    });
    
  2. Graceful Shutdown: Handle SIGTERM signal

    process.on('SIGTERM', async () => {
      console.log('SIGTERM received, shutting down gracefully');
      await server.close();
      await db.close();
      process.exit(0);
    });
    
  3. Environment Variable Separation: No hardcoding; use .env files

Prohibited Rules (MUST NOT)

  1. No Committing Secrets: Never commit API keys or passwords to Git
  2. No Debug Mode in Production: NODE_ENV=production is required
  3. Avoid latest tag only: Use version tags (v1.0.0, sha-abc123)

Best practices

  1. Multi-stage Docker builds: Minimize image size
  2. Immutable infrastructure: Redeploy instead of modifying servers
  3. Blue-Green deployment: Zero-downtime deployment and easy rollback
  4. Monitoring required: Prometheus, Grafana, Datadog

References

Metadata

Version

  • Current Version: 1.0.0
  • Last Updated: 2025-01-01
  • Compatible Platforms: Claude, ChatGPT, Gemini

Related Skills

Tags

#deployment #CI/CD #Docker #Kubernetes #automation #infrastructure

Examples

Example 1: Basic usage

Example 2: Advanced usage

Frequently asked questions

What to verify before installation and use

What does the deployment-automation source document cover?

Automate application deployment to cloud platforms and servers. Handles GitHub Actions, Docker, Kubernetes, AWS, Vercel, and deployment best practices.

How do I install deployment-automation?

The source record exposes this install command: npx skills add https://github.com/aAAaqwq/AGI-Super-Team --skill "skills/deployment-automation". Inspect the command and pinned source before running it.

Which permission-related actions were detected?

Static rules flagged exec-script, network in the source; the page lists the matching lines and excerpts.

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