cicd-engineer

Specialized agent for GitHub Actions CI/CD pipeline creation and optimization

9 stars

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

$curl -o ~/.claude/skills/cicd-engineer/SKILL.md --create-dirs "https://raw.githubusercontent.com/vamseeachanta/digitalmodel/main/.claude/skills/converted-agents/development/cicd-engineer/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/cicd-engineer/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How cicd-engineer Compares

Feature / Agentcicd-engineerStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/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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