ci-cd-generator_skill

Overview

This skill generates production-ready CI/CD pipelines for GitHub Actions, GitLab CI, Azure DevOps, and Jenkins. It produces builds, tests, deployments, caching, and secret management configured for typical full-stack and container workflows. The outputs are practical pipeline templates you can adapt to your project structure and cloud targets.

How this skill works

Provide the repository layout, languages, and target platform and the skill emits a complete pipeline file with stages for install, linting, testing, building, artifact handling, caching, and deployment. It includes secrets wiring, conditional deploys (for main branch), job dependencies, and optional Docker build-and-push steps. Templates include sensible defaults for Node.js, .NET, Docker, and Kubernetes deployments that you can customize.

When to use it

• You need a ready-to-run CI/CD configuration for GitHub Actions, GitLab CI, Azure DevOps, or Jenkins.
• You want a consistent pipeline covering build, test, and deploy with caching and artifact handling.
• You need Docker image build-and-push with registry tagging and cache optimization.
• You want CI jobs separated by frontend/backend or service boundaries with clear dependencies.
• You need deployment steps gated to main branch and integrated secret management.

Best practices

• Specify runtime versions with variables or env to keep pipelines reproducible.
• Use job-level caches (npm, Docker layer cache) and cache keys tied to lockfiles or commit refs.
• Separate lint/typecheck/test/build into distinct jobs to speed feedback and allow parallel runs.
• Protect deploy steps with branch or environment conditions and require successful tests before deployment.
• Store sensitive values in platform secrets and reference them only in deploy steps.

Example use cases

• Full-stack repo: separate GitHub Actions jobs for web (Node.js) and API (.NET) with a final Azure Web App deploy.
• GitLab CI pipeline for Node app: caching node_modules, coverage reporting, Docker build and push to registry, and kubectl image update.
• Docker-centric workflow: build-and-push action using registry tags for latest and commit SHA with build cache to speed subsequent runs.
• Monorepo scenario: per-package test jobs that run in parallel, followed by a centralized build and release job.
• CI for Kubernetes deploys: build image, push to registry, then update deployment image via kubectl or GitOps trigger.