Agent skill · DevOps & Cloud

ci-cd-pipeline-builder

Generate pragmatic CI/CD pipelines from detected project stack signals — fast baseline generation, repeatable checks, environment-aware deployment stages. Use when setting up CI for a new project, refactoring existing pipelines, or standardizing deployment workflows across multiple repos.

Alireza Rezvani23,369★ · +428/wk · 1 repos on radarProfile →
claude-codecodexcursorships scriptsMIT
Install
npx skills add alirezarezvani/claude-skills --skill ci-cd-pipeline-builder --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 8
SKILL.md size: 3 KB
Bundled scripts: yes
Path: engineering/skills/ci-cd-pipeline-builder/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 23,791 · +422 this week
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# CI/CD Pipeline Builder **Tier:** POWERFUL **Category:** Engineering **Domain:** DevOps / Automation ## Overview Use this skill to generate pragmatic CI/CD pipelines from detected project stack signals, not guesswork. It focuses on fast baseline generation, repeatable checks, and environment-aware deployment stages. ## Core Capabilities - Detect language/runtime/tooling from repository files - Recommend CI stages (`lint`, `test`, `build`, `deploy`) - Generate GitHub Actions or GitLab CI starter pipelines - Include caching and matrix strategy based on detected stack - Emit machine-readable detection output for automation - Keep pipeline logic aligned with project lockfiles and build commands ## When to Use - Bootstrapping CI for a new repository - Replacing brittle copied pipeline files - Migrating between GitHub Actions and GitLab CI - Auditing whether pipeline steps match actual stack - Creating a reproducible baseline before custom hardening ## Key Workflows ### 1. Detect Stack ```bash python3 scripts/stack_detector.py --repo . --format text python3 scripts/stack_detector.py --repo . --format json > detected-stack.json ``` Supports input via stdin or `--input` file for offline a

What's inside
Steps it walks through
  1. Overview
  2. Core Capabilities
  3. When to Use
  4. Key Workflows
  5. 1. Detect Stack
  6. 2. Generate Pipeline From Detection
  7. 3. Validate Before Merge
  8. 4. Add Deployment Stages Safely
  9. Script Interfaces
  10. References
Ships with 7 files
  • README.md
  • references/deployment-gates.md
  • references/github-actions-templates.md
  • references/gitlab-ci-templates.md
  • references/pipeline-design-notes.md
  • scripts/pipeline_generator.py
  • scripts/stack_detector.py
Commands it runs
python3 scripts/stack_detector.py --repo . --format text
python3 scripts/stack_detector.py --repo . --format json > detected-stack.json
python3 scripts/pipeline_generator.py \
python3 scripts/pipeline_generator.py --repo . --platform gitlab --output .gitlab-ci.yml
More from claude-skills
All skills →
About this skill
What does the ci-cd-pipeline-builder skill do?

Generate pragmatic CI/CD pipelines from detected project stack signals — fast baseline generation, repeatable checks, environment-aware deployment stages. Use when setting up CI for a new project, refactoring existing pipelines, or standardizing deployment workflows across multiple repos.

How do I install it?

Run `npx skills add alirezarezvani/claude-skills --skill ci-cd-pipeline-builder --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From alirezarezvani/claude-skills, a repository with 23,791 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going