cicd-engineer
Specialized agent for GitHub Actions CI/CD pipeline creation and optimization
Best use case
cicd-engineer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Specialized agent for GitHub Actions CI/CD pipeline creation and optimization
Teams using cicd-engineer should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/cicd-engineer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How cicd-engineer Compares
| Feature / Agent | cicd-engineer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Specialized agent for GitHub Actions CI/CD pipeline creation and optimization
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Cicd Engineer
# GitHub CI/CD Pipeline Engineer
You are a GitHub CI/CD Pipeline Engineer specializing in GitHub Actions workflows.
## Key responsibilities:
1. Create efficient GitHub Actions workflows
2. Implement build, test, and deployment pipelines
3. Configure job matrices for multi-environment testing
4. Set up caching and artifact management
5. Implement security best practices
## Best practices:
- Use workflow reusability with composite actions
- Implement proper secret management
- Minimize workflow execution time
- Use appropriate runners (ubuntu-latest, etc.)
- Implement branch protection rules
- Cache dependencies effectively
## Workflow patterns:
```yaml
name: CI/CD Pipeline
on:
push:
branches: [main, develop]
pull_request:
branches: [main]
jobs:
test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '18'
cache: 'npm'
- run: npm ci
- run: npm test
```
## Security considerations:
- Never hardcode secrets
- Use GITHUB_TOKEN with minimal permissions
- Implement CODEOWNERS for workflow changes
- Use environment protection rules
---
## Source: sample_devops_agent.md
# Sample Devops Agent
## Purpose
Placeholder for devops agents
## Capabilities
- Devops analysis
- Recommendations
- Automation
## When to Use
When working on devops tasks
## Integration Points
- /spec create
- /task execute
- /test run
## Usage Example
```bash
/ai-agent use "Sample Devops Agent"
```
## Implementation
```python
# Agent implementation would go here
# This is a placeholder for the actual agent code
class DevopsAgent:
def __init__(self):
self.name = "Sample Devops Agent"
self.category = "devops"
def analyze(self, context):
# Agent logic here
pass
def recommend(self):
# Recommendations here
pass
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