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Using Babysitter with Claude Code GitHub Actions reference

This guide explains how to integrate the Babysitter plugin with Claude Code GitHub Actions(https://github.com/anthropics/claude-code-action) for automated orchestration workflows in your CI/CD pipeline.

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Using Babysitter with Claude Code GitHub Actions

This guide explains how to integrate the Babysitter plugin with Claude Code GitHub Actions for automated orchestration workflows in your CI/CD pipeline.

Overview

The Babysitter plugin enables deterministic, event-sourced workflow orchestration for Claude Code. When combined with GitHub Actions, you can automate complex multi-step development processes with quality gates, human approval checkpoints, and iterative refinement.

Quick Start

Basic Setup

Add the Babysitter plugin to your GitHub Actions workflow:

yaml

name: Claude Code with Babysitter

on:
  issue_comment:
    types: [created]
  pull_request_review_comment:
    types: [created]
  issues:
    types: [opened, assigned]
  pull_request_review:
    types: [submitted]

jobs:
  claude:
    if: |
      (github.event_name == 'issue_comment' && contains(github.event.comment.body, '@claude')) ||
      (github.event_name == 'pull_request_review_comment' && contains(github.event.comment.body, '@claude')) ||
      (github.event_name == 'pull_request_review' && contains(github.event.review.body, '@claude')) ||
      (github.event_name == 'issues' && contains(github.event.issue.body, '@claude'))
    runs-on: ubuntu-latest
    permissions:
      contents: write
      pull-requests: write
      issues: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 1

      - name: Run Claude Code with Babysitter
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}

          # Add the Babysitter plugin marketplace
          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          # Install the Babysitter plugin
          plugins: |
            babysitter@a5c.ai

For comprehensive setup instructions, see the Claude Code Action Setup Guide.

Configuration Options

Plugin Marketplace

The Babysitter plugin is available from the a5c.ai marketplace:

yaml

plugin_marketplaces: |
  https://github.com/a5c-ai/babysitter.git

Plugin Installation

Install the plugin using its marketplace identifier:

yaml

plugins: |
  babysitter@a5c.ai

Workflow Examples

See the official Claude Code Action examples for additional workflow patterns.

Example 1: PR Review with Quality Gates

Use Babysitter to orchestrate comprehensive PR reviews with progress tracking:

yaml

name: Babysitter PR Review

on:
  pull_request:
    types: [opened, synchronize, ready_for_review, reopened]

jobs:
  review:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      pull-requests: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 1

      - name: Run Babysitter PR Review
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call orchestrate a thorough code review using TDD Quality Convergence methodology.

            REPO: ${{ github.repository }}
            PR NUMBER: ${{ github.event.pull_request.number }}

            Analyze the PR changes for:
            - Code quality and best practices
            - Security vulnerabilities
            - Performance implications
            - Test coverage

            Generate a structured review report with:
            - Summary of changes
            - Issues found (critical, warning, info)
            - Recommendations

Example 2: Feature Development with TDD

Automate test-driven development when issues are labeled:

yaml

name: Babysitter TDD Feature

on:
  issues:
    types: [labeled]

jobs:
  develop:
    if: github.event.label.name == 'feature-request'
    runs-on: ubuntu-latest
    timeout-minutes: 30
    permissions:
      contents: write
      pull-requests: write
      issues: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter TDD
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call implement the feature described in this issue using TDD Quality Convergence methodology.

            REPO: ${{ github.repository }}
            ISSUE NUMBER: ${{ github.event.issue.number }}

            The process should:
            1. Write failing tests first
            2. Implement minimal code to pass tests
            3. Refactor for quality
            4. Iterate until 80% quality threshold is met

            Create a PR when complete.

Example 3: Spec-Driven Development

For projects with governance requirements using manual dispatch:

yaml

name: Babysitter Spec-Kit

on:
  workflow_dispatch:
    inputs:
      spec_file:
        description: 'Path to specification file'
        required: true
        type: string

jobs:
  implement:
    runs-on: ubuntu-latest
    timeout-minutes: 60
    permissions:
      contents: write
      pull-requests: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter Spec-Kit
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call implement the specification at ${{ inputs.spec_file }} using Spec-Kit methodology.

            Follow the spec-driven approach:
            1. Parse and validate the specification
            2. Generate implementation plan
            3. Implement with continuous spec validation
            4. Generate compliance report

Example 4: GSD Quick Tasks

For rapid prototyping triggered by issue comments:

yaml

name: Babysitter GSD

on:
  issue_comment:
    types: [created]

jobs:
  gsd:
    if: contains(github.event.comment.body, '/gsd')
    runs-on: ubuntu-latest
    timeout-minutes: 15
    permissions:
      contents: write
      pull-requests: write
      issues: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 1

      - name: Run Babysitter GSD
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          allowed_non_write_users: "*"
          github_token: ${{ secrets.GITHUB_TOKEN }}

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use GSD methodology for the following task:

            ${{ github.event.comment.body }}

            Focus on rapid, working implementation with minimal overhead.

Process Library Examples

Babysitter includes a comprehensive process library with specialized processes for different domains. Use the specializations/<domain>/<process> syntax to invoke specific processes.

Available Specializations

Specialization	Description	Example Processes
`devops-sre-platform`	DevOps, SRE, Platform Engineering	cicd-pipeline-setup, kubernetes-setup, incident-response
`qa-testing-automation`	Testing and Quality Assurance	automation-framework, e2e-test-suite, performance-testing
`security-compliance`	Security and Compliance	sast-pipeline, penetration-testing, gdpr-compliance
`data-science-ml`	Data Science and Machine Learning	ml-project-scoping, model-training-pipeline, feature-engineering
`data-engineering-analytics`	Data Engineering	etl-pipeline, data-warehouse, streaming-analytics
`technical-documentation`	Documentation	adr-docs, runbook-docs, arch-docs-c4
`ux-ui-design`	UX/UI Design	design-system, accessibility-audit, usability-testing
`software-architecture`	Architecture	microservices-design, api-design, system-design

Example 5: CI/CD Pipeline Setup

Orchestrate a complete CI/CD pipeline implementation:

yaml

name: Babysitter CI/CD Setup

on:
  workflow_dispatch:
    inputs:
      target_environment:
        description: 'Target environment (dev, staging, prod)'
        required: true
        type: choice
        options:
          - dev
          - staging
          - prod

jobs:
  setup-cicd:
    runs-on: ubuntu-latest
    timeout-minutes: 45
    permissions:
      contents: write
      pull-requests: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter CI/CD Pipeline Setup
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use specializations/devops-sre-platform/cicd-pipeline-setup process.

            REPO: ${{ github.repository }}
            TARGET ENVIRONMENT: ${{ inputs.target_environment }}

            Set up a complete CI/CD pipeline with:
            - Build and test stages
            - Security scanning (SAST, dependency scanning)
            - Artifact management
            - Deployment to ${{ inputs.target_environment }}
            - Rollback capabilities

Example 6: Test Automation Framework

Orchestrate a comprehensive test automation framework setup:

yaml

name: Babysitter Test Automation

on:
  issues:
    types: [labeled]

jobs:
  setup-automation:
    if: github.event.label.name == 'setup-testing'
    runs-on: ubuntu-latest
    timeout-minutes: 60
    permissions:
      contents: write
      pull-requests: write
      issues: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter Test Automation Setup
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use specializations/qa-testing-automation/automation-framework process.

            REPO: ${{ github.repository }}
            ISSUE NUMBER: ${{ github.event.issue.number }}

            Set up a test automation framework with:
            - Page Object Model architecture
            - Unit, integration, and E2E test structure
            - CI/CD pipeline integration
            - Test reporting and metrics
            - Cross-browser testing support

            Create a PR with the framework implementation.

Example 7: Security Compliance (SAST Pipeline)

Automate security scanning pipeline setup:

yaml

name: Babysitter Security Setup

on:
  workflow_dispatch:
  schedule:
    - cron: '0 0 * * 1'  # Weekly on Monday

jobs:
  security-setup:
    runs-on: ubuntu-latest
    timeout-minutes: 30
    permissions:
      contents: write
      pull-requests: write
      security-events: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter SAST Pipeline Setup
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use specializations/security-compliance/sast-pipeline process.

            REPO: ${{ github.repository }}

            Implement a SAST (Static Application Security Testing) pipeline:
            - Code scanning with CodeQL or Semgrep
            - Dependency vulnerability scanning
            - Secret detection
            - Security findings reporting
            - Integration with GitHub Security tab

Example 8: ML Model Training Pipeline

Orchestrate ML model training workflows:

yaml

name: Babysitter ML Training

on:
  workflow_dispatch:
    inputs:
      model_type:
        description: 'Model type'
        required: true
        type: string
      dataset_path:
        description: 'Path to training dataset'
        required: true
        type: string

jobs:
  ml-training:
    runs-on: ubuntu-latest
    timeout-minutes: 120
    permissions:
      contents: write
      pull-requests: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter ML Training Pipeline
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use specializations/data-science-ml/model-training-pipeline process.

            REPO: ${{ github.repository }}
            MODEL TYPE: ${{ inputs.model_type }}
            DATASET: ${{ inputs.dataset_path }}

            Implement a model training pipeline:
            - Data validation and preprocessing
            - Feature engineering
            - Model training with hyperparameter tuning
            - Model evaluation and metrics
            - Artifact storage and versioning
            - Experiment tracking

Example 9: Incident Response Automation

Automate incident response procedures:

yaml

name: Babysitter Incident Response

on:
  issues:
    types: [opened, labeled]

jobs:
  incident-response:
    if: contains(github.event.issue.labels.*.name, 'incident')
    runs-on: ubuntu-latest
    timeout-minutes: 30
    permissions:
      contents: read
      issues: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 1

      - name: Run Babysitter Incident Response
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use specializations/devops-sre-platform/incident-response process.

            REPO: ${{ github.repository }}
            INCIDENT ISSUE: ${{ github.event.issue.number }}
            INCIDENT TITLE: ${{ github.event.issue.title }}

            Execute incident response procedure:
            - Analyze the incident description
            - Identify affected systems and severity
            - Generate investigation runbook
            - Create communication templates
            - Document timeline and action items

Example 10: Architecture Documentation

Generate architecture documentation using C4 model:

yaml

name: Babysitter Architecture Docs

on:
  workflow_dispatch:
  push:
    paths:
      - 'src/**'
      - 'packages/**'

jobs:
  generate-docs:
    runs-on: ubuntu-latest
    timeout-minutes: 30
    permissions:
      contents: write
      pull-requests: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter Architecture Documentation
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use specializations/technical-documentation/arch-docs-c4 process.

            REPO: ${{ github.repository }}

            Generate architecture documentation:
            - C4 model diagrams (Context, Container, Component)
            - System overview and dependencies
            - Data flow documentation
            - API documentation
            - Update docs/ directory with generated content

            Create a PR with the documentation updates.

Environment Variables

Configure Babysitter behavior through environment variables:

yaml

- uses: anthropics/claude-code-action@v1
  with:
    anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}

    plugin_marketplaces: |
      https://github.com/a5c-ai/babysitter.git

    plugins: |
      babysitter@a5c.ai

  env:
    # Keep runs under the checked-out repository for easy artifact upload
    BABYSITTER_RUNS_SCOPE: repo

    # Set maximum iterations (default: 65000)
    BABYSITTER_MAX_ITERATIONS: 100

    # Set quality threshold (default: 80)
    BABYSITTER_QUALITY_THRESHOLD: 85

    # Enable verbose logging
    BABYSITTER_LOG_LEVEL: debug

Artifacts and Outputs

Preserving Run State

Save Babysitter run artifacts for debugging:

yaml

- uses: actions/upload-artifact@v4
  if: always()
  with:
    name: babysitter-runs
    path: .a5c/runs/
    retention-days: 7

Run Outputs

Access run results in subsequent steps:

yaml

- uses: anthropics/claude-code-action@v1
  id: babysitter
  with:
    # ... configuration ...

- name: Check results
  run: |
    echo "Run completed"
    ls -la .a5c/runs/

Best Practices

1. Pin Plugin Versions

For reproducible builds, consider pinning to specific versions:

yaml

plugins: |
  babysitter@a5c.ai@4.0.128

2. Set Reasonable Iteration Limits

Prevent runaway workflows:

yaml

env:
  BABYSITTER_MAX_ITERATIONS: 50

3. Use Appropriate Methodologies

Use Case	Methodology
Quick prototypes	GSD
Quality-focused	TDD Quality Convergence
Compliance required	Spec-Kit
Team coordination	Scrum/Agile

4. Handle Failures Gracefully

yaml

- uses: anthropics/claude-code-action@v1
  id: babysitter
  continue-on-error: true
  with:
    # ... configuration ...

- name: Handle failure
  if: steps.babysitter.outcome == 'failure'
  run: |
    echo "Babysitter run failed - check artifacts"

Troubleshooting

Plugin Not Loading

1. Verify marketplace URL is accessible 2. Check plugin name spelling 3. Review action logs for installation errors

Runs Timing Out

1. Reduce BABYSITTER_MAX_ITERATIONS 2. Use simpler methodology (GSD vs TDD) 3. Break task into smaller pieces

Permission Errors

Ensure workflow has required permissions:

yaml

permissions:
  contents: write      # For commits
  pull-requests: write # For PR comments
  issues: write        # For issue comments

Claude Code Action

Setup Guide - Complete setup instructions
Workflow Examples - Official workflow examples
Claude Code Action Repository

Babysitter Plugin

Using Babysitter with Claude Code GitHub Actions reference

Page nodewiki/docs/github-actions-setup-claude-code.mdNearby pages · 23Documents · 0

Using Babysitter with Claude Code GitHub Actions

This guide explains how to integrate the Babysitter plugin with Claude Code GitHub Actions for automated orchestration workflows in your CI/CD pipeline.

Overview

Quick Start

Basic Setup

Add the Babysitter plugin to your GitHub Actions workflow:

yaml

name: Claude Code with Babysitter

on:
  issue_comment:
    types: [created]
  pull_request_review_comment:
    types: [created]
  issues:
    types: [opened, assigned]
  pull_request_review:
    types: [submitted]

jobs:
  claude:
    if: |
      (github.event_name == 'issue_comment' && contains(github.event.comment.body, '@claude')) ||
      (github.event_name == 'pull_request_review_comment' && contains(github.event.comment.body, '@claude')) ||
      (github.event_name == 'pull_request_review' && contains(github.event.review.body, '@claude')) ||
      (github.event_name == 'issues' && contains(github.event.issue.body, '@claude'))
    runs-on: ubuntu-latest
    permissions:
      contents: write
      pull-requests: write
      issues: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 1

      - name: Run Claude Code with Babysitter
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}

          # Add the Babysitter plugin marketplace
          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          # Install the Babysitter plugin
          plugins: |
            babysitter@a5c.ai

For comprehensive setup instructions, see the Claude Code Action Setup Guide.

Configuration Options

Plugin Marketplace

The Babysitter plugin is available from the a5c.ai marketplace:

yaml

plugin_marketplaces: |
  https://github.com/a5c-ai/babysitter.git

Plugin Installation

Install the plugin using its marketplace identifier:

yaml

plugins: |
  babysitter@a5c.ai

Workflow Examples

See the official Claude Code Action examples for additional workflow patterns.

Example 1: PR Review with Quality Gates

Use Babysitter to orchestrate comprehensive PR reviews with progress tracking:

yaml

name: Babysitter PR Review

on:
  pull_request:
    types: [opened, synchronize, ready_for_review, reopened]

jobs:
  review:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      pull-requests: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 1

      - name: Run Babysitter PR Review
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call orchestrate a thorough code review using TDD Quality Convergence methodology.

            REPO: ${{ github.repository }}
            PR NUMBER: ${{ github.event.pull_request.number }}

            Analyze the PR changes for:
            - Code quality and best practices
            - Security vulnerabilities
            - Performance implications
            - Test coverage

            Generate a structured review report with:
            - Summary of changes
            - Issues found (critical, warning, info)
            - Recommendations

Example 2: Feature Development with TDD

Automate test-driven development when issues are labeled:

yaml

name: Babysitter TDD Feature

on:
  issues:
    types: [labeled]

jobs:
  develop:
    if: github.event.label.name == 'feature-request'
    runs-on: ubuntu-latest
    timeout-minutes: 30
    permissions:
      contents: write
      pull-requests: write
      issues: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter TDD
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call implement the feature described in this issue using TDD Quality Convergence methodology.

            REPO: ${{ github.repository }}
            ISSUE NUMBER: ${{ github.event.issue.number }}

            The process should:
            1. Write failing tests first
            2. Implement minimal code to pass tests
            3. Refactor for quality
            4. Iterate until 80% quality threshold is met

            Create a PR when complete.

Example 3: Spec-Driven Development

For projects with governance requirements using manual dispatch:

yaml

name: Babysitter Spec-Kit

on:
  workflow_dispatch:
    inputs:
      spec_file:
        description: 'Path to specification file'
        required: true
        type: string

jobs:
  implement:
    runs-on: ubuntu-latest
    timeout-minutes: 60
    permissions:
      contents: write
      pull-requests: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter Spec-Kit
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call implement the specification at ${{ inputs.spec_file }} using Spec-Kit methodology.

            Follow the spec-driven approach:
            1. Parse and validate the specification
            2. Generate implementation plan
            3. Implement with continuous spec validation
            4. Generate compliance report

Example 4: GSD Quick Tasks

For rapid prototyping triggered by issue comments:

yaml

name: Babysitter GSD

on:
  issue_comment:
    types: [created]

jobs:
  gsd:
    if: contains(github.event.comment.body, '/gsd')
    runs-on: ubuntu-latest
    timeout-minutes: 15
    permissions:
      contents: write
      pull-requests: write
      issues: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 1

      - name: Run Babysitter GSD
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          allowed_non_write_users: "*"
          github_token: ${{ secrets.GITHUB_TOKEN }}

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use GSD methodology for the following task:

            ${{ github.event.comment.body }}

            Focus on rapid, working implementation with minimal overhead.

Process Library Examples

Babysitter includes a comprehensive process library with specialized processes for different domains. Use the specializations/<domain>/<process> syntax to invoke specific processes.

Available Specializations

Specialization	Description	Example Processes
`devops-sre-platform`	DevOps, SRE, Platform Engineering	cicd-pipeline-setup, kubernetes-setup, incident-response
`qa-testing-automation`	Testing and Quality Assurance	automation-framework, e2e-test-suite, performance-testing
`security-compliance`	Security and Compliance	sast-pipeline, penetration-testing, gdpr-compliance
`data-science-ml`	Data Science and Machine Learning	ml-project-scoping, model-training-pipeline, feature-engineering
`data-engineering-analytics`	Data Engineering	etl-pipeline, data-warehouse, streaming-analytics
`technical-documentation`	Documentation	adr-docs, runbook-docs, arch-docs-c4
`ux-ui-design`	UX/UI Design	design-system, accessibility-audit, usability-testing
`software-architecture`	Architecture	microservices-design, api-design, system-design

Example 5: CI/CD Pipeline Setup

Orchestrate a complete CI/CD pipeline implementation:

yaml

name: Babysitter CI/CD Setup

on:
  workflow_dispatch:
    inputs:
      target_environment:
        description: 'Target environment (dev, staging, prod)'
        required: true
        type: choice
        options:
          - dev
          - staging
          - prod

jobs:
  setup-cicd:
    runs-on: ubuntu-latest
    timeout-minutes: 45
    permissions:
      contents: write
      pull-requests: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter CI/CD Pipeline Setup
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use specializations/devops-sre-platform/cicd-pipeline-setup process.

            REPO: ${{ github.repository }}
            TARGET ENVIRONMENT: ${{ inputs.target_environment }}

            Set up a complete CI/CD pipeline with:
            - Build and test stages
            - Security scanning (SAST, dependency scanning)
            - Artifact management
            - Deployment to ${{ inputs.target_environment }}
            - Rollback capabilities

Example 6: Test Automation Framework

Orchestrate a comprehensive test automation framework setup:

yaml

name: Babysitter Test Automation

on:
  issues:
    types: [labeled]

jobs:
  setup-automation:
    if: github.event.label.name == 'setup-testing'
    runs-on: ubuntu-latest
    timeout-minutes: 60
    permissions:
      contents: write
      pull-requests: write
      issues: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter Test Automation Setup
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use specializations/qa-testing-automation/automation-framework process.

            REPO: ${{ github.repository }}
            ISSUE NUMBER: ${{ github.event.issue.number }}

            Set up a test automation framework with:
            - Page Object Model architecture
            - Unit, integration, and E2E test structure
            - CI/CD pipeline integration
            - Test reporting and metrics
            - Cross-browser testing support

            Create a PR with the framework implementation.

Example 7: Security Compliance (SAST Pipeline)

Automate security scanning pipeline setup:

yaml

name: Babysitter Security Setup

on:
  workflow_dispatch:
  schedule:
    - cron: '0 0 * * 1'  # Weekly on Monday

jobs:
  security-setup:
    runs-on: ubuntu-latest
    timeout-minutes: 30
    permissions:
      contents: write
      pull-requests: write
      security-events: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter SAST Pipeline Setup
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use specializations/security-compliance/sast-pipeline process.

            REPO: ${{ github.repository }}

            Implement a SAST (Static Application Security Testing) pipeline:
            - Code scanning with CodeQL or Semgrep
            - Dependency vulnerability scanning
            - Secret detection
            - Security findings reporting
            - Integration with GitHub Security tab

Example 8: ML Model Training Pipeline

Orchestrate ML model training workflows:

yaml

name: Babysitter ML Training

on:
  workflow_dispatch:
    inputs:
      model_type:
        description: 'Model type'
        required: true
        type: string
      dataset_path:
        description: 'Path to training dataset'
        required: true
        type: string

jobs:
  ml-training:
    runs-on: ubuntu-latest
    timeout-minutes: 120
    permissions:
      contents: write
      pull-requests: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter ML Training Pipeline
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use specializations/data-science-ml/model-training-pipeline process.

            REPO: ${{ github.repository }}
            MODEL TYPE: ${{ inputs.model_type }}
            DATASET: ${{ inputs.dataset_path }}

            Implement a model training pipeline:
            - Data validation and preprocessing
            - Feature engineering
            - Model training with hyperparameter tuning
            - Model evaluation and metrics
            - Artifact storage and versioning
            - Experiment tracking

Example 9: Incident Response Automation

Automate incident response procedures:

yaml

name: Babysitter Incident Response

on:
  issues:
    types: [opened, labeled]

jobs:
  incident-response:
    if: contains(github.event.issue.labels.*.name, 'incident')
    runs-on: ubuntu-latest
    timeout-minutes: 30
    permissions:
      contents: read
      issues: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 1

      - name: Run Babysitter Incident Response
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use specializations/devops-sre-platform/incident-response process.

            REPO: ${{ github.repository }}
            INCIDENT ISSUE: ${{ github.event.issue.number }}
            INCIDENT TITLE: ${{ github.event.issue.title }}

            Execute incident response procedure:
            - Analyze the incident description
            - Identify affected systems and severity
            - Generate investigation runbook
            - Create communication templates
            - Document timeline and action items

Example 10: Architecture Documentation

Generate architecture documentation using C4 model:

yaml

name: Babysitter Architecture Docs

on:
  workflow_dispatch:
  push:
    paths:
      - 'src/**'
      - 'packages/**'

jobs:
  generate-docs:
    runs-on: ubuntu-latest
    timeout-minutes: 30
    permissions:
      contents: write
      pull-requests: write
      id-token: write
    steps:
      - name: Checkout repository
        uses: actions/checkout@v6
        with:
          fetch-depth: 0

      - name: Run Babysitter Architecture Documentation
        uses: anthropics/claude-code-action@v1
        with:
          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
          track_progress: true

          plugin_marketplaces: |
            https://github.com/a5c-ai/babysitter.git

          plugins: |
            babysitter@a5c.ai

          prompt: |
            /babysitter:call use specializations/technical-documentation/arch-docs-c4 process.

            REPO: ${{ github.repository }}

            Generate architecture documentation:
            - C4 model diagrams (Context, Container, Component)
            - System overview and dependencies
            - Data flow documentation
            - API documentation
            - Update docs/ directory with generated content

            Create a PR with the documentation updates.

Environment Variables

Configure Babysitter behavior through environment variables:

yaml

- uses: anthropics/claude-code-action@v1
  with:
    anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}

    plugin_marketplaces: |
      https://github.com/a5c-ai/babysitter.git

    plugins: |
      babysitter@a5c.ai

  env:
    # Keep runs under the checked-out repository for easy artifact upload
    BABYSITTER_RUNS_SCOPE: repo

    # Set maximum iterations (default: 65000)
    BABYSITTER_MAX_ITERATIONS: 100

    # Set quality threshold (default: 80)
    BABYSITTER_QUALITY_THRESHOLD: 85

    # Enable verbose logging
    BABYSITTER_LOG_LEVEL: debug

Artifacts and Outputs

Preserving Run State

Save Babysitter run artifacts for debugging:

yaml

- uses: actions/upload-artifact@v4
  if: always()
  with:
    name: babysitter-runs
    path: .a5c/runs/
    retention-days: 7

Run Outputs

Access run results in subsequent steps:

yaml

- uses: anthropics/claude-code-action@v1
  id: babysitter
  with:
    # ... configuration ...

- name: Check results
  run: |
    echo "Run completed"
    ls -la .a5c/runs/

Best Practices

1. Pin Plugin Versions

For reproducible builds, consider pinning to specific versions:

yaml

plugins: |
  babysitter@a5c.ai@4.0.128

2. Set Reasonable Iteration Limits

Prevent runaway workflows:

yaml

env:
  BABYSITTER_MAX_ITERATIONS: 50

3. Use Appropriate Methodologies

Use Case	Methodology
Quick prototypes	GSD
Quality-focused	TDD Quality Convergence
Compliance required	Spec-Kit
Team coordination	Scrum/Agile

4. Handle Failures Gracefully

yaml

- uses: anthropics/claude-code-action@v1
  id: babysitter
  continue-on-error: true
  with:
    # ... configuration ...

- name: Handle failure
  if: steps.babysitter.outcome == 'failure'
  run: |
    echo "Babysitter run failed - check artifacts"

Troubleshooting

Plugin Not Loading

1. Verify marketplace URL is accessible 2. Check plugin name spelling 3. Review action logs for installation errors

Runs Timing Out

1. Reduce BABYSITTER_MAX_ITERATIONS 2. Use simpler methodology (GSD vs TDD) 3. Break task into smaller pieces

Permission Errors

Ensure workflow has required permissions:

yaml

permissions:
  contents: write      # For commits
  pull-requests: write # For PR comments
  issues: write        # For issue comments

Claude Code Action

Setup Guide - Complete setup instructions
Workflow Examples - Official workflow examples
Claude Code Action Repository

Using Babysitter with Claude Code GitHub Actions reference

Continue reading

Using Babysitter with Claude Code GitHub Actions

Overview

Quick Start

Basic Setup

Configuration Options

Plugin Marketplace

Plugin Installation

Workflow Examples

Example 1: PR Review with Quality Gates

Example 2: Feature Development with TDD

Example 3: Spec-Driven Development

Example 4: GSD Quick Tasks

Process Library Examples

Available Specializations

Example 5: CI/CD Pipeline Setup

Example 6: Test Automation Framework

Example 7: Security Compliance (SAST Pipeline)

Example 8: ML Model Training Pipeline

Example 9: Incident Response Automation

Example 10: Architecture Documentation

Environment Variables

Artifacts and Outputs

Preserving Run State

Run Outputs

Best Practices

1. Pin Plugin Versions

2. Set Reasonable Iteration Limits

3. Use Appropriate Methodologies

4. Handle Failures Gracefully

Troubleshooting

Plugin Not Loading

Runs Timing Out

Permission Errors

Related Documentation

Claude Code Action

Babysitter Plugin

Using Babysitter with Claude Code GitHub Actions reference

Continue reading

Using Babysitter with Claude Code GitHub Actions

Overview

Quick Start

Basic Setup

Configuration Options

Plugin Marketplace

Plugin Installation

Workflow Examples

Example 1: PR Review with Quality Gates

Example 2: Feature Development with TDD

Example 3: Spec-Driven Development

Example 4: GSD Quick Tasks

Process Library Examples

Available Specializations

Example 5: CI/CD Pipeline Setup

Example 6: Test Automation Framework

Example 7: Security Compliance (SAST Pipeline)

Example 8: ML Model Training Pipeline

Example 9: Incident Response Automation

Example 10: Architecture Documentation

Environment Variables

Artifacts and Outputs

Preserving Run State

Run Outputs

Best Practices

1. Pin Plugin Versions

2. Set Reasonable Iteration Limits

3. Use Appropriate Methodologies

4. Handle Failures Gracefully

Troubleshooting

Plugin Not Loading

Runs Timing Out

Permission Errors

Related Documentation

Claude Code Action

Babysitter Plugin