بنقرة واحدة
ci-generate
Generate CI/CD pipeline configurations for GitHub Actions, GitLab CI, CircleCI, or Jenkins.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
القائمة
Generate CI/CD pipeline configurations for GitHub Actions, GitLab CI, CircleCI, or Jenkins.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Headless browser automation CLI optimized for AI agents. Uses snapshot + refs system for 93% less context overhead vs Playwright. Purpose-built for web testing, form automation, screenshots, and data extraction.
Manage a gitflow branching workflow — starting and finishing feature, release, and hotfix branches; cutting versioned releases with changelog generation; coordinating emergency hotfixes directly to production; and keeping long-lived branches in sync. Activates when users mention gitflow, feature/release/hotfix branches, cutting a release, branching strategy, promoting an integration branch to production, tagging a version, or rolling back a live release. Also reaches for it when the user says "ship it", "promote dev to main", or "we need to hotfix prod" without naming gitflow. Skip for general git mechanics (commit messages, merge conflicts, interactive rebase, git education) or CI-failure debugging unrelated to a release.
Fixes a bug through test-driven debugging — reproduces it with a failing test, locates the root cause with evidence (file:line), then applies the smallest fix that resolves it without refactoring unrelated code. Use when the user wants to fix a bug, debug an issue, resolve an error, or investigate a failing test. Not for building new functionality (use implement-feature) or restructuring working code with no bug involved (use refactor).
Implements a new feature end-to-end as a senior staff engineer would — discovers project conventions, researches current best practices, drafts a plan for approval, then builds it with parallel subagents that reuse existing code, skip speculative abstractions, and verify with tests before completion. Use when the user wants to implement, build, add, or ship new functionality (a feature, endpoint, component, module, or integration) — not for fixing an existing bug (use fix-bug) or restructuring code that already works (use refactor).
Restructures existing code without changing its behavior — maps callers and test coverage, adds characterization tests where coverage is thin, then applies the change in small steps verified against the full test suite after each one. Use when the user wants to refactor, extract a method or class, simplify logic, reduce duplication, improve naming, restructure modules, or pay down technical debt in code that already works. Not for adding new functionality (use implement-feature) or fixing broken behavior (use fix-bug).
Runs a comprehensive multi-agent code review of a PR, commit, or the whole codebase across six dimensions (correctness, performance, code style, test coverage, error handling, and simplicity/over-engineering) and returns a severity-ranked report with file:line findings and fix suggestions. Use when the user wants a thorough code review, asks to review a PR or diff, or wants over-engineered code flagged for simplification. Analysis only, identifying issues without modifying code, committing, or running tests. Not for a security-focused audit (use review-security) or a visual/UX design critique (use review-design).
| name | ci-generate |
| description | Generate CI/CD pipeline configurations for GitHub Actions, GitLab CI, CircleCI, or Jenkins. |
| metadata | {"author":"mgiovani","version":"1.0.0","source":"https://github.com/mgiovani/skills"} |
| disable-model-invocation | true |
Cross-Platform AI Agent Skill This skill works with any AI agent platform that supports the skills.sh standard.
Generate production-ready CI/CD pipeline configurations with auto-detected project stack, current best practices, and comprehensive stages (lint, test, build, security scan, deploy).
command arguments
CRITICAL: Pipeline configurations must match ACTUAL project tooling:
package.json scripts, Makefile targets, pyproject.toml scripts before referencing them.node-version, .python-version, pyproject.toml, etc.)Extract configuration from command arguments:
Arguments:
- <platform>: Target CI platform (default: auto-detect from existing config)
- "github" or "gh": GitHub Actions
- "gitlab" or "gl": GitLab CI
- "circle" or "circleci": CircleCI
- "jenkins": Jenkins (Jenkinsfile)
- "--deploy <target>": Deployment target (optional)
- "vercel", "netlify", "aws", "gcp", "azure", "docker", "k8s", "fly", "railway"
- "--monorepo": Generate matrix/path-filtered workflows
- No args: Auto-detect platform from existing CI config files, default to GitHub Actions
If no platform specified, detect from existing files:
- `.github/workflows/*.yml` → GitHub Actions
- `.gitlab-ci.yml` → GitLab CI
- `.circleci/config.yml` → CircleCI
- `Jenkinsfile` → Jenkins
- No CI config found → Default to GitHub Actions
### Phase 1: Project Stack Detection
Explore the codebase to discover the complete project technology stack:
### Phase 2: Research Best Practices
Search for current CI/CD best practices for the detected stack:
Use WebSearch:
Use WebSearch:
Based on discovery and research, design the pipeline with these stages:
Standard Stages (always include):
ruff check, eslint, golangci-lint)ruff format --check, prettier --check)pyright, tsc --noEmit, mypy)npm run build, cargo build --release)--deploy specified or deployment config detected)Design Decisions:
Generate the complete CI/CD configuration file based on the designed architecture.
For platform-specific syntax and patterns, consult:
File Locations by Platform:
| Platform | File Path |
|---|---|
| GitHub Actions | .github/workflows/ci.yml |
| GitLab CI | .gitlab-ci.yml |
| CircleCI | .circleci/config.yml |
| Jenkins | Jenkinsfile |
Generation Guidelines:
latest)If an existing CI config exists:
Step 5.1: Syntax Validation
Validate the generated configuration:
# GitHub Actions - validate YAML structure
python3 -c "import yaml; yaml.safe_load(open('.github/workflows/ci.yml'))"
# GitLab CI - validate if gitlab-ci-lint available
# gitlab-ci-lint .gitlab-ci.yml
# CircleCI - validate if circleci CLI available
# circleci config validate
# General YAML validation
python3 -c "import yaml; yaml.safe_load(open('<config_file>'))"
**Step 5.2: Cross-Reference Check**
Verify all referenced commands and paths exist:
1. Every script/command in the pipeline exists in the project
2. Every referenced file path is valid
3. Service versions match project requirements
4. Environment variable names are consistent
**Step 5.3: Present Summary**
Output a summary including:
- Pipeline architecture overview
- Stages and their purposes
- Trigger conditions (which branches, PR events)
- Estimated run time per stage
- Required secrets/environment variables to configure
- Cache strategy explanation
- Any manual steps needed (e.g., setting up deployment secrets)
## Platform Quick Reference
### GitHub Actions
- **Triggers**: `push`, `pull_request`, `workflow_dispatch`, `schedule`
- **Runners**: `ubuntu-latest`, `ubuntu-24.04`, `macos-latest`, `windows-latest`
- **Caching**: `actions/cache@v4` or built-in package manager caching
- **Artifacts**: `actions/upload-artifact@v4`, `actions/download-artifact@v4`
- **Secrets**: `${{ secrets.SECRET_NAME }}`
- **Matrix**: `strategy.matrix` for multi-version testing
### GitLab CI
- **Stages**: Defined globally, jobs assigned to stages
- **Caching**: Per-job or global cache with keys
- **Artifacts**: Job artifacts with expiry
- **Variables**: `variables:` block or CI/CD settings
- **Rules**: `rules:` for conditional execution
- **Services**: `services:` for database containers
### CircleCI
- **Executors**: Docker, machine, macOS
- **Orbs**: Reusable config packages (e.g., `node`, `python`, `docker`)
- **Workflows**: Named workflow with job dependencies
- **Caching**: `save_cache`/`restore_cache` with keys
- **Contexts**: Shared environment variables
### Jenkins
- **Pipeline**: Declarative or scripted
- **Stages**: Named stages with steps
- **Agent**: Docker, node labels
- **Post**: Always/success/failure actions
- **Credentials**: `credentials` for secrets
- **Parallel**: `parallel` block for concurrent stages
## Handling Ambiguity
If encountering unclear requirements:
1. Use `interactive clarification` to clarify platform choice, deployment target, or branching strategy
2. Present options with trade-offs when multiple valid approaches exist
3. Default to the most common configuration for the detected stack
## Usage Examples
```bash
# Auto-detect everything
ci-generate
# Specify platform
ci-generate github
ci-generate gitlab
ci-generate circleci
ci-generate jenkins
# With deployment target
ci-generate github --deploy vercel
ci-generate gitlab --deploy docker
ci-generate github --deploy aws
# Monorepo support
ci-generate github --monorepo
# Combined options
ci-generate github --deploy k8s --monorepo
## Important Notes
- **Discover first**: Never assume project tooling; always run Phase 1
- **Pin versions**: Use specific versions for actions, orbs, images, and tools
- **Secrets documentation**: List all required secrets so users know what to configure
- **Existing config**: Always check for and respect existing CI configuration
- **Security by default**: Include dependency scanning and secret detection in every pipeline
- **Cache effectively**: Proper caching can reduce CI times by 50-80%