cicd-pipeline-generator
This skill should be used when creating or configuring CI/CD pipeline files for automated testing, building, and deployment. Use this for generating GitHub Actions workflows, GitLab CI configs, CircleCI configs, or other CI/CD platform configurations. Ideal for setting up automated pipelines for Node.js/Next.js applications, including linting, testing, building, and deploying to platforms like Vercel, Netlify, or AWS.
Install
mkdir -p .claude/skills/cicd-pipeline-generator && curl -L -o skill.zip "https://mcp.directory/api/skills/download/3197" && unzip -o skill.zip -d .claude/skills/cicd-pipeline-generator && rm skill.zipInstalls to .claude/skills/cicd-pipeline-generator
About this skill
CI/CD Pipeline Generator
Overview
Generate production-ready CI/CD pipeline configuration files for various platforms (GitHub Actions, GitLab CI, CircleCI, Jenkins). This skill provides templates and guidance for setting up automated workflows that handle linting, testing, building, and deployment for modern web applications, particularly Node.js/Next.js projects.
Core Capabilities
1. Platform Selection
Choose the appropriate CI/CD platform based on project requirements:
- GitHub Actions: Best for GitHub-hosted projects with native integration
- GitLab CI/CD: Ideal for GitLab repositories with complex pipeline needs
- CircleCI: Optimized for Docker workflows and fast build times
- Jenkins: Suitable for self-hosted, highly customizable environments
Refer to references/platform-comparison.md for detailed platform comparisons, pros/cons, and use case recommendations.
2. Pipeline Configuration Generation
Generate pipeline configs following these principles:
Pipeline Stages
Structure pipelines with these standard stages:
-
Install Dependencies
- Checkout code from repository
- Setup runtime environment (Node.js version)
- Restore cached dependencies
- Install dependencies with
npm ci - Cache dependencies for future runs
-
Lint
- Run ESLint for code quality
- Run TypeScript type checking
- Fail fast on linting errors
-
Test
- Execute unit tests
- Execute integration tests
- Generate code coverage reports
- Upload coverage to reporting services (Codecov, Coveralls)
-
Build
- Create production build
- Verify build succeeds
- Store build artifacts
-
Deploy
- Deploy to staging (develop branch)
- Deploy to production (main branch)
- Run post-deployment smoke tests
Caching Strategy
Implement effective caching to speed up builds:
# Cache node_modules based on package-lock.json
cache:
key: ${{ hashFiles('package-lock.json') }}
paths:
- node_modules/
- .npm/
Environment Variables
Configure necessary environment variables:
NODE_ENV: Set toproductionfor builds- Platform-specific tokens: Store as secrets
- Build-time variables: Pass to build process
3. Template Usage
Use provided templates from assets/ directory:
GitHub Actions Template (assets/github-actions-nodejs.yml):
- Multi-job workflow with lint, test, build, deploy
- Matrix builds for multiple Node.js versions (optional)
- Vercel deployment integration
- Artifact uploading
- Code coverage reporting
GitLab CI Template (assets/gitlab-ci-nodejs.yml):
- Multi-stage pipeline
- Dependency caching
- Manual production deployment
- Automatic staging deployment
- Coverage reporting
To use a template:
- Copy the appropriate template file
- Place in the correct location:
- GitHub Actions:
.github/workflows/ci.yml - GitLab CI:
.gitlab-ci.yml
- GitHub Actions:
- Customize deployment targets, environment variables, and branch names
- Add required secrets to platform settings
4. Deployment Configuration
Vercel Deployment
For GitHub Actions:
- uses: amondnet/vercel-action@v25
with:
vercel-token: ${{ secrets.VERCEL_TOKEN }}
vercel-org-id: ${{ secrets.VERCEL_ORG_ID }}
vercel-project-id: ${{ secrets.VERCEL_PROJECT_ID }}
vercel-args: '--prod'
Required Secrets:
VERCEL_TOKEN: Get from Vercel account settingsVERCEL_ORG_ID: From Vercel project settingsVERCEL_PROJECT_ID: From Vercel project settings
Netlify Deployment
- run: |
npm install -g netlify-cli
netlify deploy --prod --dir=.next
env:
NETLIFY_AUTH_TOKEN: ${{ secrets.NETLIFY_AUTH_TOKEN }}
NETLIFY_SITE_ID: ${{ secrets.NETLIFY_SITE_ID }}
AWS S3 + CloudFront
- uses: aws-actions/configure-aws-credentials@v4
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: us-east-1
- run: |
aws s3 sync .next/static s3://${{ secrets.S3_BUCKET }}/static
aws cloudfront create-invalidation --distribution-id ${{ secrets.CF_DIST_ID }} --paths "/*"
5. Testing Integration
Configure test execution with proper reporting:
Jest Configuration:
- name: Run tests with coverage
run: npm test -- --coverage --coverageReporters=text --coverageReporters=lcov
- name: Upload coverage
uses: codecov/codecov-action@v4
with:
files: ./coverage/lcov.info
flags: unittests
Fail Fast Strategy:
# Run quick tests first
jobs:
lint: # Fails in ~30 seconds
test: # Fails in ~2 minutes
build: # Fails in ~5 minutes
needs: [lint, test]
deploy:
needs: [build]
6. Branch-Based Workflows
Implement different behaviors per branch:
Feature Branches / PRs:
- Run lint + test only
- No deployment
- Add PR comments with test results
Develop Branch:
- Run lint + test + build
- Deploy to staging environment
- Automatic deployment
Main Branch:
- Run lint + test + build
- Deploy to production
- Manual approval (optional)
- Create release tags
Example:
deploy_staging:
if: github.ref == 'refs/heads/develop'
# Deploy to staging
deploy_production:
if: github.ref == 'refs/heads/main'
environment: production # Requires manual approval
# Deploy to production
Workflow Decision Tree
Follow this decision tree to generate the appropriate pipeline:
-
Which platform?
- GitHub → Use
assets/github-actions-nodejs.yml - GitLab → Use
assets/gitlab-ci-nodejs.yml - CircleCI/Jenkins → Adapt GitHub Actions template
- Unsure → Consult
references/platform-comparison.md
- GitHub → Use
-
What stages are needed?
- Always include: Lint, Test, Build
- Optional: Security scanning, E2E tests, performance tests
- Add deployment stage if deploying from CI
-
Which deployment platform?
- Vercel → Use Vercel deployment examples
- Netlify → Use Netlify CLI approach
- AWS → Use AWS Actions/CLI
- Custom → Implement custom deployment script
-
What triggers?
- On push to main/develop
- On pull request
- On tag creation
- Manual workflow dispatch
-
What environment variables needed?
- Platform tokens (Vercel, Netlify, AWS)
- API keys for external services
- Build-time environment variables
- Feature flags
Best Practices
Security
- Store all secrets in platform secret management (never in code)
- Use least-privilege tokens (read-only when possible)
- Rotate secrets regularly
- Audit secret access permissions
- Never log secrets (use
***masking)
Performance
- Cache dependencies aggressively
- Parallelize independent jobs
- Use matrix builds for multi-version testing
- Fail fast: Run quick checks before slow ones
- Optimize Docker layer caching
Reliability
- Pin exact Node.js versions (
18.xnot just18) - Commit lockfiles (
package-lock.json) - Add retry logic for flaky external services
- Set reasonable timeouts (10-15 minutes max)
- Use
continue-on-errorfor non-critical steps
Maintainability
- Add comments explaining complex logic
- Use reusable workflows/templates
- Keep configs DRY (Don't Repeat Yourself)
- Version control all pipeline changes
- Document required secrets in README
Common Patterns
Multi-Environment Deployment
deploy_staging:
environment: staging
if: github.ref == 'refs/heads/develop'
deploy_production:
environment: production
if: github.ref == 'refs/heads/main'
needs: [deploy_staging]
Matrix Testing
strategy:
matrix:
node-version: [16.x, 18.x, 20.x]
os: [ubuntu-latest, windows-latest]
Conditional Steps
- name: Deploy
if: github.event_name == 'push' && github.ref == 'refs/heads/main'
run: npm run deploy
Artifact Management
- name: Upload build
uses: actions/upload-artifact@v4
with:
name: build-output
path: .next/
retention-days: 7
- name: Download build
uses: actions/download-artifact@v4
with:
name: build-output
Troubleshooting
Pipeline Failures
- Check action/job logs for error messages
- Verify environment variables and secrets are set
- Test commands locally before adding to pipeline
- Check for platform-specific issues in documentation
Slow Builds
- Verify cache is working (check cache hit/miss logs)
- Parallelize independent jobs
- Use faster runners if available
- Optimize dependency installation
Deployment Failures
- Verify deployment tokens are valid
- Check platform status pages
- Review deployment logs
- Test deployment commands locally
Resources
Templates (assets/)
github-actions-nodejs.yml: Complete GitHub Actions workflowgitlab-ci-nodejs.yml: Complete GitLab CI pipeline
Reference Documentation (references/)
platform-comparison.md: Detailed comparison of CI/CD platforms, deployment targets, best practices, and common patterns
Example Usage
User Request: "Create a GitHub Actions workflow that runs tests and deploys to Vercel"
Steps:
- Copy
assets/github-actions-nodejs.ymltemplate - Create
.github/workflows/directory if it doesn't exist - Save as
.github/workflows/ci.yml - Update deployment section with Vercel credentials
- Add secrets to GitHub repository settings:
VERCEL_TOKENVERCEL_ORG_IDVERCEL_PROJECT_ID
- Commit and push to trigger workflow
User Request: "Set up GitLab CI with staging and production environments"
Steps:
- Copy
assets/gitlab-ci-nodejs.ymltemplate - Save as
.gitlab-ci.ymlin repository root - Configure GitLab CI/CD variables:
VERCEL_TOKEN- Other deployment credentials
- Review manual approval settings for production
- Commit to trigger pipeline
Advanced Configuration
Monorepo Support
paths:
- 'apps/frontend/**'
- 'packages/**'
Scheduled Runs
on:
schedule:
---
*Content truncated.*
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