Agent skill

Cicd Pipeline Generator

by ailabs-393 in ailabs-393/ai-labs-claude-skills

This skill should be used when creating or configuring CI/CD pipeline files for automated testing, building, and deployment.

MITAuto-check passedDevOps & Cloud

Install Cicd Pipeline Generator

skills CLI
$ npx skills add ailabs-393/ai-labs-claude-skills --skill cicd-pipeline-generator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ailabs-393/ai-labs-claude-skills cicd-pipeline-generator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ailabs-393/ai-labs-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/skills/cicd-pipeline-generator .claude/skills/cicd-pipeline-generator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
cicd-pipeline-generator
GitHub stars
455
Token cost
~2.7k tokens
SKILL.md length
881 words
Files
6 (incl. references, assets)
Skills in repo
22
Repo updated
First seen
Licence
MIT

At a glance

This skill should be used when creating or configuring CI/CD pipeline files for automated testing, building, and deployment.

  • Works in 6 steps: Platform Selection → Pipeline Configuration Generation → Template Usage → …
  • Tasks that involve CI/CD
  • SKILL.md covers Overview, Core Capabilities, Workflow Decision Tree and Best Practices, plus 5 more sections
  • Runs JavaScript scripts from its folder; calls npm; needs VERCEL_TOKEN and NETLIFY_AUTH_TOKEN

What it does

Cicd Pipeline Generator is an agent skill from ailabs-393/ai-labs-claude-skills. 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.

Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files and assets (for example `assets/github-actions-nodejs.yml`, `assets/gitlab-ci-nodejs.yml` and `index.js`).

It sits in DevOps & Cloud, covering CI/CD. It works with GitLab, Node.js, GitHub Actions and Netlify. The repository describes itself as: This package is use to remove the hustle of finding claudeskills and shift them into any of the user project. This project become a bridge between user's usage and claude skills. The licence is MIT.

When your agent uses it

  • Tasks that involve CI/CD

Example prompts

  • “/cicd-pipeline-generator”

Requirements

  • Node.js
  • Docker
  • A credential in VERCEL_TOKEN
  • A credential in NETLIFY_AUTH_TOKEN

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Platform Selection
  2. Pipeline Configuration Generation
  3. Template Usage
  4. Deployment Configuration
  5. Testing Integration
  6. Branch-Based Workflows

What it can do on your machine

Read from SKILL.md and the folder at commit 1a12bc7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (JavaScript), which the agent can run.

    Shell commands in SKILL.md call:

    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • VERCEL_TOKEN
    • NETLIFY_AUTH_TOKEN
    • SNYK_TOKEN
    • AWS_ACCESS_KEY_ID
    • AWS_SECRET_ACCESS_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cicd Pipeline Generator loads about 2.7k tokens when it runs, and up to ~4.5k if it reads all its reference files. Until then it costs about 111 tokens; SKILL.md has 881 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~111
When it runs · the whole SKILL.md, loaded when a task matches
~2.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ailabs-393/ai-labs-claude-skills at commit 1a12bc7, republished under its MIT licence (© ailabs-393). 881 words, ~2,730 tokens.

Download SKILL.mdSave it as .claude/skills/cicd-pipeline-generator/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
cicd-pipeline-generator
description
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.

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:

  1. 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
  2. Lint

    • Run ESLint for code quality
    • Run TypeScript type checking
    • Fail fast on linting errors
  3. Test

    • Execute unit tests
    • Execute integration tests
    • Generate code coverage reports
    • Upload coverage to reporting services (Codecov, Coveralls)
  4. Build

    • Create production build
    • Verify build succeeds
    • Store build artifacts
  5. 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:

yaml
# 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 to production for 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:

  1. Copy the appropriate template file
  2. Place in the correct location:
    • GitHub Actions: .github/workflows/ci.yml
    • GitLab CI: .gitlab-ci.yml
  3. Customize deployment targets, environment variables, and branch names
  4. Add required secrets to platform settings
4. Deployment Configuration
Vercel Deployment

For GitHub Actions:

yaml
- 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 settings
  • VERCEL_ORG_ID: From Vercel project settings
  • VERCEL_PROJECT_ID: From Vercel project settings
Netlify Deployment
yaml
- 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
yaml
- 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:

yaml
- 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:

yaml
# 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:

yaml
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:

  1. 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
  2. What stages are needed?

    • Always include: Lint, Test, Build
    • Optional: Security scanning, E2E tests, performance tests
    • Add deployment stage if deploying from CI
  3. Which deployment platform?

    • Vercel → Use Vercel deployment examples
    • Netlify → Use Netlify CLI approach
    • AWS → Use AWS Actions/CLI
    • Custom → Implement custom deployment script
  4. What triggers?

    • On push to main/develop
    • On pull request
    • On tag creation
    • Manual workflow dispatch
  5. What environment variables needed?

    • Platform tokens (Vercel, Netlify, AWS)
    • API keys for external services
    • Build-time environment variables
    • Feature flags
Show full SKILL.md (342 more words)Show less

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.x not just 18)
  • Commit lockfiles (package-lock.json)
  • Add retry logic for flaky external services
  • Set reasonable timeouts (10-15 minutes max)
  • Use continue-on-error for 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
yaml
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
yaml
strategy:
  matrix:
    node-version: [16.x, 18.x, 20.x]
    os: [ubuntu-latest, windows-latest]
Conditional Steps
yaml
- name: Deploy
  if: github.event_name == 'push' && github.ref == 'refs/heads/main'
  run: npm run deploy
Artifact Management
yaml
- 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
  1. Check action/job logs for error messages
  2. Verify environment variables and secrets are set
  3. Test commands locally before adding to pipeline
  4. Check for platform-specific issues in documentation
Slow Builds
  1. Verify cache is working (check cache hit/miss logs)
  2. Parallelize independent jobs
  3. Use faster runners if available
  4. Optimize dependency installation
Deployment Failures
  1. Verify deployment tokens are valid
  2. Check platform status pages
  3. Review deployment logs
  4. Test deployment commands locally

Resources

Templates (assets/)
  • github-actions-nodejs.yml: Complete GitHub Actions workflow
  • gitlab-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:

  1. Copy assets/github-actions-nodejs.yml template
  2. Create .github/workflows/ directory if it doesn't exist
  3. Save as .github/workflows/ci.yml
  4. Update deployment section with Vercel credentials
  5. Add secrets to GitHub repository settings:
    • VERCEL_TOKEN
    • VERCEL_ORG_ID
    • VERCEL_PROJECT_ID
  6. Commit and push to trigger workflow

User Request: "Set up GitLab CI with staging and production environments"

Steps:

  1. Copy assets/gitlab-ci-nodejs.yml template
  2. Save as .gitlab-ci.yml in repository root
  3. Configure GitLab CI/CD variables:
    • VERCEL_TOKEN
    • Other deployment credentials
  4. Review manual approval settings for production
  5. Commit to trigger pipeline

Advanced Configuration

Monorepo Support
yaml
paths:
  - 'apps/frontend/**'
  - 'packages/**'
Scheduled Runs
yaml
on:
  schedule:
    - cron: '0 2 * * *'  # Daily at 2 AM
External Service Integration
yaml
- name: Notify Slack
  uses: 8398a7/action-slack@v3
  with:
    status: ${{ job.status }}
    webhook_url: ${{ secrets.SLACK_WEBHOOK }}
Security Scanning
yaml
- name: Run security audit
  run: npm audit --audit-level=moderate

- name: Check for vulnerabilities
  uses: snyk/actions/node@master
  env:
    SNYK_TOKEN: ${{ secrets.SNYK_TOKEN }}

© ailabs-393, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (references, assets) in packages/skills/cicd-pipeline-generator of ailabs-393/ai-labs-claude-skills.

  • SKILL.md
  • assets/github-actions-nodejs.yml
  • assets/gitlab-ci-nodejs.yml
  • index.js
  • package.json
  • references/platform-comparison.md

Open the folder on GitHubat commit 1a12bc7

Compare with similar skills

Cicd Pipeline Generator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Cicd Pipeline Generator compared with similar skills
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Cicd Pipeline Generator this skillailabs-393/ai-labs-claude-skills455—~2.7kAutomated safety check: PassMIT
Deployments Cicdvercel/vercel-plugin3011 repos~3kAutomated safety check: PassCustom licence
Deploy Release Testvercel/next.js143k—~1.2kAutomated safety check: PassMIT
Deploy Setupgarrytan/gstack136k—~11kAutomated safety check: NotesMIT
CI/CD Pipeline Principlesirahardianto/awesome-agv156—~2.7kAutomated safety check: NotesMIT
Memstack Deployment CI CD Pipelinecwinvestments/memstack423—~3.9kAutomated safety check: NotesProprietary

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Categories

Questions about Cicd Pipeline Generator

What does Cicd Pipeline Generator do?

This skill should be used when creating or configuring CI/CD pipeline files for automated testing, building, and deployment. Cicd Pipeline Generator is an agent skill from ailabs-393/ai-labs-claude-skills. This skill should be used when creating or configuring CI/CD pipeline files for automated testing, building, and deployment.

When should I use Cicd Pipeline Generator?

Cicd Pipeline Generator fits situations like: tasks that involve CI/CD.

How do I install Cicd Pipeline Generator in Claude Code?

Run `npx skills add ailabs-393/ai-labs-claude-skills --skill cicd-pipeline-generator -a claude-code`. Or copy the skill folder (packages/skills/cicd-pipeline-generator in ailabs-393/ai-labs-claude-skills) into .claude/skills/cicd-pipeline-generator in your project. Claude Code loads it when a task matches its description.

How do I install Cicd Pipeline Generator in Codex?

Run `npx skills add ailabs-393/ai-labs-claude-skills --skill cicd-pipeline-generator -a codex`. Or copy the skill folder (packages/skills/cicd-pipeline-generator in ailabs-393/ai-labs-claude-skills) into .agents/skills/cicd-pipeline-generator in your project. Codex loads it when a task matches its description.

Can I use Cicd Pipeline Generator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ailabs-393/ai-labs-claude-skills --skill cicd-pipeline-generator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cicd-pipeline-generator, .gemini/skills/cicd-pipeline-generator, .github/skills/cicd-pipeline-generator and .opencode/skills/cicd-pipeline-generator in your project.

What does Cicd Pipeline Generator need to run?

Going by SKILL.md and its folder, Cicd Pipeline Generator needs JavaScript for the scripts in its folder, the command-line tools its instructions call (npm) and credentials named VERCEL_TOKEN, NETLIFY_AUTH_TOKEN, SNYK_TOKEN and AWS_ACCESS_KEY_ID. Our summary lists: Node.js; Docker; A credential in VERCEL_TOKEN; A credential in NETLIFY_AUTH_TOKEN.

Does Cicd Pipeline Generator access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Cicd Pipeline Generator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Cicd Pipeline Generator use?

Cicd Pipeline Generator is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cicd Pipeline Generator use?

About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.8k tokens, read only when the agent opens those files.

What are the alternatives to Cicd Pipeline Generator?

Skills that share tags, products or a category with Cicd Pipeline Generator: Deployments Cicd (vercel/vercel-plugin, 301 stars), Deploy Release Test (vercel/next.js, 143k stars), Deploy Setup (garrytan/gstack, 136k stars) and CI/CD Pipeline Principles (irahardianto/awesome-agv, 156 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cicd Pipeline Generator?

ailabs-393 (a GitHub user) maintains it in ailabs-393/ai-labs-claude-skills, which has 455 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on November 11, 2025.

Source: ailabs-393/ai-labs-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.