gitlab-cicd-pipeline
Design and implement GitLab CI/CD pipelines with stages, jobs, artifacts, and caching. Configure runners, Docker integration, and deployment strategies.
- Installs
- 664
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill gitlab-cicd-pipeline- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads gitlab-cicd-pipeline automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
GitLab CI/CD Pipeline
Table of Contents
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 | Complete Pipeline Configuration |
| GitLab Runner Configuration | GitLab Runner Configuration |
| Docker Layer Caching Optimization | Docker Layer Caching Optimization |
| Multi-Project Pipeline | Multi-Project Pipeline |
| Kubernetes Deployment | 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
onlyandexcept - 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
FAQ
What does the gitlab-cicd-pipeline skill do?
Design and implement GitLab CI/CD pipelines with stages, jobs, artifacts, and caching. Configure runners, Docker integration, and deployment strategies.
How do I install gitlab-cicd-pipeline?
Run npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill gitlab-cicd-pipeline in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/gitlab-cicd-pipeline/ (personal) or .claude/skills/gitlab-cicd-pipeline/ (project).
Which AI agents can use gitlab-cicd-pipeline?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is gitlab-cicd-pipeline safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains gitlab-cicd-pipeline?
It is published by aj-geddes in aj-geddes/useful-ai-prompts. It has 664 recorded installs.
More from aj-geddes/useful-ai-prompts
nodejs-express-server
aj-geddes/useful-ai-prompts
Build production-ready Express.js servers with middleware, authentication, routing, and database integration. Use when creating REST APIs, managing requests/responses, implementing middleware chains, and handling server logic.
code-review-analysis
aj-geddes/useful-ai-prompts
Perform comprehensive code reviews with best practices, security checks, and constructive feedback. Use when reviewing pull requests, analyzing code quality, checking for security vulnerabilities, or providing code improvement suggestions.
rest-api-design
aj-geddes/useful-ai-prompts
Design RESTful APIs following best practices for resource modeling, HTTP methods, status codes, versioning, and documentation. Use when creating new APIs, designing endpoints, or improving existing API architecture.
jenkins-pipeline
aj-geddes/useful-ai-prompts
Build Jenkins declarative and scripted pipelines with stages, agents, parameters, and plugins. Implement multi-branch pipelines and deployment automation.
architecture-diagrams
aj-geddes/useful-ai-prompts
Create system architecture diagrams using Mermaid, PlantUML, C4 model, flowcharts, and sequence diagrams. Use when documenting architecture, system design, data flows, or technical workflows.
ansible-automation
aj-geddes/useful-ai-prompts
Infrastructure automation and configuration management using Ansible playbooks, roles, and inventory. Use for deploying applications, patching, and managing servers.
Popular devops & cloud skills
microsoft-foundry
microsoft/azure-skills
Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, managed harness agent create, GitHub Copilot harness agent, create agent, update agent, add tool to agent, invoke agent, agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure
azure-diagnostics
microsoft/azure-skills
Debug Azure production issues on Azure using AppLens, Azure Monitor, resource health, and safe triage. WHEN: debug production issues, troubleshoot app service, app service high CPU, app service deployment failure, troubleshoot container apps, container app 503 or target port mismatch, troubleshoot functions, function telemetry missing or stopped after a config/connection-string change, troubleshoot AKS, VM RDP, Linux SSH, VM black screen, can't connect to VM, reset VM password, NSG or firewall blocking, kubectl cannot connect, kube-system/CoreDNS failures, pod pending, crashloop, node not ready, upgrade failures, analyze logs, KQL, insights, image pull failures, cold start issues, health probe failures, resource health, root cause of errors, troubleshoot event hubs, troubleshoot service bus, messaging SDK error, AMQP connection failure, message lock lost, lock renewal during long-running processing, service bus dead letter.
azure-prepare
microsoft/azure-skills
Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.
azure-ai
microsoft/azure-skills
Use for Azure AI: Search, Speech, OpenAI, Document Intelligence. Helps with search, vector/hybrid search, speech-to-text, text-to-speech, transcription, OCR. WHEN: AI Search, query search, vector search, hybrid search, semantic search, speech-to-text, text-to-speech, transcribe, OCR, convert text to speech.
azure-deploy
microsoft/azure-skills
Execute Azure deployments for ALREADY-PREPARED applications that have existing .azure/deployment-plan.md and infrastructure files. DO NOT use this skill when the user asks to CREATE a new application — use azure-prepare instead. This skill runs azd up, azd deploy, terraform apply, and az deployment commands with built-in error recovery. Requires .azure/deployment-plan.md from azure-prepare and validated status from azure-validate. WHEN: "run azd up", "run azd deploy", "execute deployment", "push to production", "push to cloud", "go live", "ship it", "bicep deploy", "terraform apply", "publish to Azure", "launch on Azure". DO NOT USE WHEN: "create and deploy", "build and deploy", "create a new app", "set up infrastructure", "create and deploy to Azure using Terraform" — use azure-prepare for these.
azure-validate
microsoft/azure-skills
Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.