/gitlab-cicd-pipeline
Design and implement GitLab CI/CD pipelines with stages, jobs, artifacts, and caching. Configure runners, Docker integration, and deployment strategies.
$ npx -y skills add aj-geddes/useful-ai-prompts --skill gitlab-cicd-pipeline --agent claude-codeHow it fires
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- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/gitlab-cicd-pipeline
Context preview
The summary Claude sees to decide when to auto-load this skill.
Design and implement GitLab CI/CD pipelines with stages, jobs, artifacts, and caching. Configure runners, Docker integration, and deployment strategies.
SKILL.md
gitlab-cicd-pipeline.SKILL.mdname: gitlab-cicd-pipeline
description: >
Design and implement GitLab CI/CD pipelines with stages, jobs, artifacts, and
caching. Configure runners, Docker integration, and deployment strategies.
GitLab CI/CD Pipeline
Table of Contents
- [Overview](#overview)
- [When to Use](#when-to-use)
- [Quick Start](#quick-start)
- [Reference Guides](#reference-guides)
- [Best Practices](#best-practices)
Overview
Create comprehensive GitLab CI/CD pipelines that automate building, testing, and deployment using GitLab Runner infrastructure and container execution.
When to Use
- GitLab repository CI/CD setup
- Multi-stage build pipelines
- Docker registry integration
- Kubernetes deployment
- Review app deployment
- Cache optimization
- Dependency management
Quick Start
Minimal working example:
# .gitlab-ci.yml
image: node:18-alpine
variables:
DOCKER_DRIVER: overlay2
FF_USE_FASTZIP: "true"
stages:
- lint
- test
- build
- security
- deploy-review
- deploy-prod
cache:
key: ${CI_COMMIT_REF_SLUG}
paths:
- node_modules/
- .npm/
lint:
stage: lint
script:
- npm install
// ... (see reference guides for full implementation)Reference Guides
Detailed implementations in the `references/` directory:
| Guide | Contents | |---|---| | [Complete Pipeline Configuration](references/complete-pipeline-configuration.md) | Complete Pipeline Configuration | | [GitLab Runner Configuration](references/gitlab-runner-configuration.md) | GitLab Runner Configuration | | [Docker Layer Caching Optimization](references/docker-layer-caching-optimization.md) | Docker Layer Caching Optimization | | [Multi-Project Pipeline](references/multi-project-pipeline.md) | Multi-Project Pipeline | | [Kubernetes Deployment](references/kubernetes-deployment.md) | Kubernetes Deployment, Performance Testing Stage, Release Pipeline with Semantic Versioning |
Best Practices
✅ DO
- Use stages to organize pipeline flow
- Implement caching for dependencies
- Use artifacts for test reports
- Set appropriate cache keys
- Implement conditional execution with `only` and `except`
- Use `needs:` for job dependencies
- Clean up artifacts with `expire_in`
- Use Docker for consistent environments
- Implement security scanning stages
- Set resource limits for jobs
- Use merge request pipelines
❌ DON'T
- Run tests serially when parallelizable
- Cache everything unnecessarily
- Leave large artifacts indefinitely
- Store secrets in configuration files
- Run privileged Docker without necessity
- Skip security scanning
- Ignore pipeline failures
- Use `only: [main]` without proper controls
Read more
name: gitlab-cicd-pipeline description: > Design and implement GitLab CI/CD pipelines with stages, jobs, artifacts, and caching. Configure runners, Docker integration, and deployment strategies.
GitLab CI/CD Pipeline
Table of Contents
- [Overview](#overview)
- [When to Use](#when-to-use)
- [Quick Start](#quick-start)
- [Reference Guides](#reference-guides)
- [Best Practices](#best-practices)
Overview
Create comprehensive GitLab CI/CD pipelines that automate building, testing, and deployment using GitLab Runner infrastructure and container execution.
When to Use
- GitLab repository CI/CD setup
- Multi-stage build pipelines
- Docker registry integration
- Kubernetes deployment
- Review app deployment
- Cache optimization
- Dependency management
Quick Start
Minimal working example:
# .gitlab-ci.yml
image: node:18-alpine
variables:
DOCKER_DRIVER: overlay2
FF_USE_FASTZIP: "true"
stages:
- lint
- test
- build
- security
- deploy-review
- deploy-prod
cache:
key: ${CI_COMMIT_REF_SLUG}
paths:
- node_modules/
- .npm/
lint:
stage: lint
script:
- npm install
// ... (see reference guides for full implementation)Reference Guides
Detailed implementations in the `references/` directory:
| Guide | Contents | |---|---| | [Complete Pipeline Configuration](references/complete-pipeline-configuration.md) | Complete Pipeline Configuration | | [GitLab Runner Configuration](references/gitlab-runner-configuration.md) | GitLab Runner Configuration | | [Docker Layer Caching Optimization](references/docker-layer-caching-optimization.md) | Docker Layer Caching Optimization | | [Multi-Project Pipeline](references/multi-project-pipeline.md) | Multi-Project Pipeline | | [Kubernetes Deployment](references/kubernetes-deployment.md) | Kubernetes Deployment, Performance Testing Stage, Release Pipeline with Semantic Versioning |
Best Practices
✅ DO
- Use stages to organize pipeline flow
- Implement caching for dependencies
- Use artifacts for test reports
- Set appropriate cache keys
- Implement conditional execution with `only` and `except`
- Use `needs:` for job dependencies
- Clean up artifacts with `expire_in`
- Use Docker for consistent environments
- Implement security scanning stages
- Set resource limits for jobs
- Use merge request pipelines
❌ DON'T
- Run tests serially when parallelizable
- Cache everything unnecessarily
- Leave large artifacts indefinitely
- Store secrets in configuration files
- Run privileged Docker without necessity
- Skip security scanning
- Ignore pipeline failures
- Use `only: [main]` without proper controls
488 production-ready AI prompts, all following a standardized template with validated quality gates. Transform ChatGPT, Claude, and other AI assistants into expert consultants.
Repo: aj-geddes/useful-ai-prompts
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