Implement GitOps workflows with ArgoCD and Flux for automated, declarative Kubernetes...
npx skills add jon23d/skillz --skill "cicd-pipeline-creation"
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# Description
Use when creating CI/CD pipelines for any project. Use when asked to "set up CI/CD", "create a pipeline", "automate deployments", "configure GitHub Actions", "set up Vercel/Render/AWS", or similar. Apply regardless of hosting platform, language, or framework.
# SKILL.md
name: cicd-pipeline-creation
description: Use when creating CI/CD pipelines for any project. Use when asked to "set up CI/CD", "create a pipeline", "automate deployments", "configure GitHub Actions", "set up Vercel/Render/AWS", or similar. Apply regardless of hosting platform, language, or framework.
CI/CD Pipeline Creation
A CI/CD pipeline must be complete, verifiable, and safe. Every pipeline must have these elements:
Required elements
1. Test stage — runs on every push and pull request
- Install dependencies
- Run tests
- Fail if tests don't pass
2. Deploy stage — runs only after tests pass, on specific branches
- Deploy to a real hosting service (Vercel, Render, AWS, etc.)
- Not just "build and push" — actual deployment must happen
3. Verification stage — runs immediately after deploy
- Hit the health endpoint
- Confirm the service is responding
- Fail if health check fails
4. Rollback strategy — documented or automated
- If deploy fails, how do you rollback?
- Either auto-rollback or manual rollback steps documented
5. Secrets documentation — list every required secret
- What secrets are needed?
- Where are they configured?
- How do you set them up?
Common mistakes — and the responses
"I'll just push to Docker and that's the deploy."
Pushing an image is not deploying. Deploy means the service is running and accessible. You must have a step that actually deploys to a hosting service.
"I'll add health checks later."
Without verification, you don't know if the deploy succeeded. A health check is required immediately after deploy.
"Rollback is complex, I'll skip it."
Rollback is required. Either document the manual steps or implement auto-rollback. Production failures happen.
"I'll assume people know what secrets to set."
List every secret explicitly. Example: RENDER_API_KEY, VERCEL_TOKEN, AWS_ACCESS_KEY_ID. Say where to configure them (GitHub repo secrets, environment variables, etc.).
"Staging is optional."
For production safety, staging is required. Test on staging first, then promote to production.
Red flags — stop and reassess
- You created a pipeline that builds/pushes but never deploys
- You have no health check or verification after deploy
- You have no rollback strategy (documented or automated)
- You didn't list the required secrets
- You're deploying straight to production with no staging
- You assume "someone will figure out" the secrets
Checklist per pipeline
- [ ] Test stage: installs deps, runs tests, fails on test failure
- [ ] Deploy stage: deploys to actual hosting service (not just build/push)
- [ ] Verification stage: health check hits endpoint, confirms response
- [ ] Rollback strategy: documented or automated
- [ ] Secrets documented: list every secret, say where to configure
- [ ] Staging environment: test on staging before production (for production pipelines)
Example structure (GitHub Actions)
on: push, pull_request
jobs:
test:
runs-on: ubuntu-latest
steps:
- checkout
- setup-node
- npm ci
- npm test
deploy-staging:
needs: test
if: main branch push
steps:
- checkout
- deploy to staging (Vercel/Render/etc.)
- health check: GET /health, expect 200
deploy-production:
needs: deploy-staging
if: production trigger
steps:
- deploy to production
- health check: GET /health, expect 200
- rollback steps documented
Secrets documentation format
At the end of your pipeline file or in a README, list:
Required secrets:
- VERCEL_TOKEN: Vercel API token (configure in GitHub repo secrets)
- RENDER_API_KEY: Render API key (configure in GitHub repo secrets)
- SERVICE_ID: Your service ID from Vercel/Render
Setup:
1. Go to GitHub repo → Settings → Secrets and variables → Actions
2. Add each secret with the correct value
3. Verify in a test deploy
# Supported AI Coding Agents
This skill is compatible with the SKILL.md standard and works with all major AI coding agents:
Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.