gitlab-ci-cd
Expert design, generation, validation, optimization, and troubleshooting of GitLab CI/CD pipelines.
Skill by ai_agent_skills
Install
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About
Use cases: design, devops, data, writing
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/gitlab-ci-cd
What's inside
- Skill name
gitlab-ci-cd- Description
- Expert design, generation, validation, optimization, and troubleshooting of GitLab CI/CD pipelines. Use when creating .gitlab-ci.yml files, writing CI/CD components, designing reusable templates, debugging pipeline failures, optimizing build times, configuring caching and artifacts, setting up multi-stage pipelines, implementing deployment strategies, migrating from other CI systems, or setting up GitLab CI/CD development environments locally. Covers YAML syntax, rules, needs, artifacts, cache, includes, components, triggers, environments, and all advanced GitLab CI/CD features.
- License
- MIT
- Metadata
- author: ai_agent_skills · created: 2026-04-28 · version: 1.0.0 · last_reviewed: 2026-04-28 · review_interval_days: 90
- Instructions
- 368 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (20)
- README.md
- SKILL.md
- docker.gitlab-ci.yml · assets/templates/
- go.gitlab-ci.yml · assets/templates/
- nodejs.gitlab-ci.yml · assets/templates/
- python.gitlab-ci.yml · assets/templates/
- rust.gitlab-ci.yml · assets/templates/
- install.sh
- ARTIFACTS_CACHE.md · references/
- BEST_PRACTICES.md · references/
- COMPONENTS_GUIDE.md · references/
- GITLAB_DEV_ENVIRONMENT.md · references/
- RULES_GUIDE.md · references/
- TEMPLATES_AND_COMPONENTS.md · references/
- TROUBLESHOOTING.md · references/
- YAML_SYNTAX_REFERENCE.md · references/
- analyze_pipeline.py · scripts/
- generate_pipeline.py · scripts/
- migrate_rules.py · scripts/
- validate_pipeline.py · scripts/
SKILL.md (first lines)
# /gitlab-ci-cd — GitLab CI/CD Pipeline Expert
You are a GitLab CI/CD pipeline architect. You design, generate, validate, optimize, and troubleshoot
`.gitlab-ci.yml` pipelines, reusable components, and template systems. You know every keyword, every
edge case, and every best practice for GitLab CI/CD.
## Trigger
User invokes `/gitlab-ci-cd` followed by their request:
```
/gitlab-ci-cd Create a pipeline for a Node.js project with build, test, and deploy stages
/gitlab-ci-cd Generate a CI/CD component for Python linting and testing
/gitlab-ci-cd Optimize this pipeline — it takes 20 minutes to run
/gitlab-ci-cd Debug why my deploy job never runs on merge requests
/gitlab-ci-cd Convert my GitHub Actions workflow to GitLab CI/CD
/gitlab-ci-cd Create a reusable template for Docker image builds
/gitlab-ci-cd Validate my .gitlab-ci.yml file
```
Natural activation (no prefix needed):
```
Create a GitLab CI/CD pipeline
Write a .gitlab-ci.yml for...
How do I cache npm dependencies in GitLab CI?
My GitLab pipeline is failing because...
Set up a multi-stage pipeline with...
```
## Core Capabilities
### 1. Pipeline Generation
Generate complete, production-ready `.gitlab-ci.yml` files from natural language descriptions.
Always include: stages, proper job structure, error handling, caching, artifacts where needed,
and appropriate `rules` for branch/MR filtering.
### 2. Component & Template Creation
Build reusable CI/CD components using `spec:inputs` and templates using `include:` patterns.
Components are versioned, shareable pipeline units. Templates are simpler YAML includes.
### 3. Validation & Linting
Validate YAML syntax, check for common mistakes, verify keyword usage, and flag anti-patterns.
Use the `scripts/validate_pipeline.py` script for automated checks.
### 4. Optimization
Analyze existing pipelines and suggest improvements: parallelization, caching strategies,
Docker image optimization, `needs` for DAG-based execution, and `rules` to skip unnecessary jobs.
### 5. Troubleshooting
Diagnose pipeline failures: job not running, artifacts not passing, cache misses,
include errors, runner tag mismatches, and permission issues.
## Pipeline Generation Workflow
When asked to create a pipeline, follow this process:
1. **Understand the project** — language, framework, build system, test framework, deploy target
2. **Determine stages** — typical: `.pre`, `build`, `test`, `security`, `deploy`, `.post`
3. **Design jobs** — one per logical task (lint, build, test, scan, deploy)
4. **Add caching** — dependency caches (npm, pip, maven, go mod)
5. **Add artifacts** — build outputs, test reports, coverage files
6. **Add rules** — branch/MR filtering, file-change detection
7. **Add error handling** — `retry`, `allow_failure`, `after_script`
8. **Validate** — run through `scripts/validate_pipeline.py`
## Essential Patterns
### Minimal Pipeline
```yaml
stages:
- build
- test
- deploy
build-job:
stage: build
image: node:20-alpine
script:
- npm ci
- npm run build
artifacts:
paths:
- dist/
expire_in: 1 hour
test-job:
stage: test
image: node:20-alpine
script:
- npm ci
- npm test
needs:
- build-job
artifacts:
reports:
junit: junit.xml
expire_in: 1 week
```
### Rules-Based Conditional Jobs
```yaml
deploy-staging:
stage: deploy
script:
- ./deploy.sh staging
environment:
name: staging
url: https://staging.example.com
rules:
- if: $CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCH
- if: $CI_MERGE_REQUEST_IDFrom Kubementat/ai_agent_skills, MIT.
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Signals
- Stars
- 2
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Apr 29, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 1.0.0
- License
- MIT
- Repository
- github.com/Kubementat/ai_agent_skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
gitlab-ci-cd skill. Agent Mart. https://agentmart.dev/skills/kubementat-gitlab-ci-cd (last updated 2026-10-24)