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Github Workflow Automation

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ruvnet
github-workflow-automation

Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management

Overview

Publisherruvnet
RepositoryRuView
Skill namegithub-workflow-automation
Stars
97.4K
Forks
12.8K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by ruvnet on GitHub. Read the source before you install it.

Installation

Install the Github Workflow Automation AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ruvnet/RuView/tree/main/.claude/skills/github-workflow-automation
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ruvnet/RuView.git /tmp/RuView
mkdir -p .claude/skills
cp -r /tmp/RuView/.claude/skills/github-workflow-automation .claude/skills/github-workflow-automation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Github Workflow Automation in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Github Workflow Automation on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Github Workflow Automation is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

GitHub Workflow Automation Skill

Overview

This skill provides comprehensive GitHub Actions automation with AI swarm coordination. It integrates intelligent CI/CD pipelines, workflow orchestration, and repository management to create self-organizing, adaptive GitHub workflows.

Quick Start

Initialize GitHub Workflow Automation

bash
# Start with a simple workflow
npx ruv-swarm actions generate-workflow \
  --analyze-codebase \
  --detect-languages \
  --create-optimal-pipeline

Common Commands

bash
# Optimize existing workflow
npx ruv-swarm actions optimize \
  --workflow ".github/workflows/ci.yml" \
  --suggest-parallelization

# Analyze failed runs
gh run view <run-id> --json jobs,conclusion | \
  npx ruv-swarm actions analyze-failure \
    --suggest-fixes

Core Capabilities

🤖 Swarm-Powered GitHub Modes

1. gh-coordinator

GitHub workflow orchestration and coordination

  • Coordination Mode: Hierarchical
  • Max Parallel Operations: 10
  • Batch Optimized: Yes
  • Best For: Complex GitHub workflows, multi-repo coordination
bash
# Usage example
npx claude-flow@alpha github gh-coordinator \
  "Coordinate multi-repo release across 5 repositories"
2. pr-manager

Pull request management and review coordination

  • Review Mode: Automated
  • Multi-reviewer: Yes
  • Conflict Resolution: Intelligent
bash
# Create PR with automated review
gh pr create --title "Feature: New capability" \
  --body "Automated PR with swarm review" | \
  npx ruv-swarm actions pr-validate \
    --spawn-agents "linter,tester,security,docs"
3. issue-tracker

Issue management and project coordination

  • Issue Workflow: Automated
  • Label Management: Smart
  • Progress Tracking: Real-time
bash
# Create coordinated issue workflow
npx claude-flow@alpha github issue-tracker \
  "Manage sprint issues with automated tracking"
4. release-manager

Release coordination and deployment

  • Release Pipeline: Automated
  • Versioning: Semantic
  • Deployment: Multi-stage
bash
# Automated release management
npx claude-flow@alpha github release-manager \
  "Create v2.0.0 release with changelog and deployment"
5. repo-architect

Repository structure and organization

  • Structure Optimization: Yes
  • Multi-repo Support: Yes
  • Template Management: Advanced
bash
# Optimize repository structure
npx claude-flow@alpha github repo-architect \
  "Restructure monorepo with optimal organization"
6. code-reviewer

Automated code review and quality assurance

  • Review Quality: Deep
  • Security Analysis: Yes
  • Performance Check: Automated
bash
# Automated code review
gh pr view 123 --json files | \
  npx ruv-swarm actions pr-validate \
    --deep-review \
    --security-scan
7. ci-orchestrator

CI/CD pipeline coordination

  • Pipeline Management: Advanced
  • Test Coordination: Parallel
  • Deployment: Automated
bash
# Orchestrate CI/CD pipeline
npx claude-flow@alpha github ci-orchestrator \
  "Setup parallel test execution with smart caching"
8. security-guardian

Security and compliance management

  • Security Scan: Automated
  • Compliance Check: Continuous
  • Vulnerability Management: Proactive
bash
# Security audit
npx ruv-swarm actions security \
  --deep-scan \
  --compliance-check \
  --create-issues

🔧 Workflow Templates

1. Intelligent CI with Swarms
yaml
# .github/workflows/swarm-ci.yml
name: Intelligent CI with Swarms
on: [push, pull_request]

jobs:
  swarm-analysis:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3

      - name: Initialize Swarm
        uses: ruvnet/swarm-action@v1
        with:
          topology: mesh
          max-agents: 6

      - name: Analyze Changes
        run: |
          npx ruv-swarm actions analyze \
            --commit ${{ github.sha }} \
            --suggest-tests \
            --optimize-pipeline
2. Multi-Language Detection
yaml
# .github/workflows/polyglot-swarm.yml
name: Polyglot Project Handler
on: push

jobs:
  detect-and-build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3

      - name: Detect Languages
        id: detect
        run: |
          npx ruv-swarm actions detect-stack \
            --output json > stack.json

      - name: Dynamic Build Matrix
        run: |
          npx ruv-swarm actions create-matrix \
            --from stack.json \
            --parallel-builds
3. Adaptive Security Scanning
yaml
# .github/workflows/security-swarm.yml
name: Intelligent Security Scan
on:
  schedule:
    - cron: '0 0 * * *'
  workflow_dispatch:

jobs:
  security-swarm:
    runs-on: ubuntu-latest
    steps:
      - name: Security Analysis Swarm
        run: |
          SECURITY_ISSUES=$(npx ruv-swarm actions security \
            --deep-scan \
            --format json)

          echo "$SECURITY_ISSUES" | jq -r '.issues[]? | @base64' | while read -r issue; do
            _jq() {
              echo ${issue} | base64 --decode | jq -r ${1}
            }
            gh issue create \
              --title "$(_jq '.title')" \
              --body "$(_jq '.body')" \
              --label "security,critical"
          done
4. Self-Healing Pipeline
yaml
# .github/workflows/self-healing.yml
name: Self-Healing Pipeline
on: workflow_run

jobs:
  heal-pipeline:
    if: ${{ github.event.workflow_run.conclusion == 'failure' }}
    runs-on: ubuntu-latest
    steps:
      - name: Diagnose and Fix
        run: |
          npx ruv-swarm actions self-heal \
            --run-id ${{ github.event.workflow_run.id }} \
            --auto-fix-common \
            --create-pr-complex
5. Progressive Deployment
yaml
# .github/workflows/smart-deployment.yml
name: Smart Deployment
on:
  push:
    branches: [main]

jobs:
  progressive-deploy:
    runs-on: ubuntu-latest
    steps:
      - name: Analyze Risk
        id: risk
        run: |
          npx ruv-swarm actions deploy-risk \
            --changes ${{ github.sha }} \
            --history 30d

      - name: Choose Strategy
        run: |
          npx ruv-swarm actions deploy-strategy \
            --risk ${{ steps.risk.outputs.level }} \
            --auto-execute
6. Performance Regression Detection
yaml
# .github/workflows/performance-guard.yml
name: Performance Guard
on: pull_request

jobs:
  perf-swarm:
    runs-on: ubuntu-latest
    steps:
      - name: Performance Analysis
        run: |
          npx ruv-swarm actions perf-test \
            --baseline main \
            --threshold 10% \
            --auto-profile-regression
7. PR Validation Swarm
yaml
# .github/workflows/pr-validation.yml
name: PR Validation Swarm
on: pull_request

jobs:
  validate:
    runs-on: ubuntu-latest
    steps:
      - name: Multi-Agent Validation
        run: |
          PR_DATA=$(gh pr view ${{ github.event.pull_request.number }} --json files,labels)

          RESULTS=$(npx ruv-swarm actions pr-validate \
            --spawn-agents "linter,tester,security,docs" \
            --parallel \
            --pr-data "$PR_DATA")

          gh pr comment ${{ github.event.pull_request.number }} \
            --body "$RESULTS"
8. Intelligent Release
yaml
# .github/workflows/intelligent-release.yml
name: Intelligent Release
on:
  push:
    tags: ['v*']

jobs:
  release:
    runs-on: ubuntu-latest
    steps:
      - name: Release Swarm
        run: |
          npx ruv-swarm actions release \
            --analyze-changes \
            --generate-notes \
            --create-artifacts \
            --publish-smart

📊 Monitoring & Analytics

Workflow Analytics
bash
# Analyze workflow performance
npx ruv-swarm actions analytics \
  --workflow "ci.yml" \
  --period 30d \
  --identify-bottlenecks \
  --suggest-improvements
Cost Optimization
bash
# Optimize GitHub Actions costs
npx ruv-swarm actions cost-optimize \
  --analyze-usage \
  --suggest-caching \
  --recommend-self-hosted
Failure Pattern Analysis
bash
# Identify failure patterns
npx ruv-swarm actions failure-patterns \
  --period 90d \
  --classify-failures \
  --suggest-preventions
Resource Management
bash
# Optimize resource usage
npx ruv-swarm actions resources \
  --analyze-usage \
  --suggest-runners \
  --cost-optimize

Advanced Features

🧪 Dynamic Test Strategies

Smart Test Selection
yaml
# Automatically select relevant tests
- name: Swarm Test Selection
  run: |
    npx ruv-swarm actions smart-test \
      --changed-files ${{ steps.files.outputs.all }} \
      --impact-analysis \
      --parallel-safe
Dynamic Test Matrix
yaml
# Generate test matrix from code analysis
jobs:
  generate-matrix:
    outputs:
      matrix: ${{ steps.set-matrix.outputs.matrix }}
    steps:
      - id: set-matrix
        run: |
          MATRIX=$(npx ruv-swarm actions test-matrix \
            --detect-frameworks \
            --optimize-coverage)
          echo "matrix=${MATRIX}" >> $GITHUB_OUTPUT

  test:
    needs: generate-matrix
    strategy:
      matrix: ${{fromJson(needs.generate-matrix.outputs.matrix)}}
Intelligent Parallelization
bash
# Determine optimal parallelization
npx ruv-swarm actions parallel-strategy \
  --analyze-dependencies \
  --time-estimates \
  --cost-aware

🔮 Predictive Analysis

Predictive Failures
bash
# Predict potential failures
npx ruv-swarm actions predict \
  --analyze-history \
  --identify-risks \
  --suggest-preventive
Workflow Recommendations
bash
# Get workflow recommendations
npx ruv-swarm actions recommend \
  --analyze-repo \
  --suggest-workflows \
  --industry-best-practices
Automated Optimization
bash
# Continuously optimize workflows
npx ruv-swarm actions auto-optimize \
  --monitor-performance \
  --apply-improvements \
  --track-savings

🎯 Custom Actions Development

Custom Swarm Action Template
javascript
// action.yml
name: 'Swarm Custom Action'
description: 'Custom swarm-powered action'
inputs:
  task:
    description: 'Task for swarm'
    required: true
runs:
  using: 'node16'
  main: 'dist/index.js'

// index.js
const { SwarmAction } = require('ruv-swarm');

async function run() {
  const swarm = new SwarmAction({
    topology: 'mesh',
    agents: ['analyzer', 'optimizer']
  });

  await swarm.execute(core.getInput('task'));
}

run().catch(error => core.setFailed(error.message));

Integration with Claude-Flow

🔄 Swarm Coordination Patterns

Initialize GitHub Swarm
javascript
// Step 1: Initialize swarm coordination
mcp__claude-flow__swarm_init {
  topology: "hierarchical",
  maxAgents: 8
}

// Step 2: Spawn specialized agents
mcp__claude-flow__agent_spawn { type: "coordinator", name: "GitHub Coordinator" }
mcp__claude-flow__agent_spawn { type: "reviewer", name: "Code Reviewer" }
mcp__claude-flow__agent_spawn { type: "tester", name: "QA Agent" }
mcp__claude-flow__agent_spawn { type: "analyst", name: "Security Analyst" }

// Step 3: Orchestrate GitHub workflow
mcp__claude-flow__task_orchestrate {
  task: "Complete PR review and merge workflow",
  strategy: "parallel",
  priority: "high"
}
GitHub Hooks Integration
bash
# Pre-task: Setup GitHub context
npx claude-flow@alpha hooks pre-task \
  --description "PR review workflow" \
  --context "pr-123"

# During task: Track progress
npx claude-flow@alpha hooks notify \
  --message "Completed security scan" \
  --type "github-action"

# Post-task: Export results
npx claude-flow@alpha hooks post-task \
  --task-id "pr-review-123" \
  --export-github-summary

📦 Batch Operations

Parallel GitHub CLI Commands
javascript
// Single message with all GitHub operations
[Concurrent Execution]:
  Bash("gh issue create --title 'Feature A' --body 'Description A' --label 'enhancement'")
  Bash("gh issue create --title 'Feature B' --body 'Description B' --label 'enhancement'")
  Bash("gh pr create --title 'PR 1' --head 'feature-a' --base 'main'")
  Bash("gh pr create --title 'PR 2' --head 'feature-b' --base 'main'")
  Bash("gh pr checks 123 --watch")
  TodoWrite { todos: [
    {content: "Review security scan results", status: "pending"},
    {content: "Merge approved PRs", status: "pending"},
    {content: "Update changelog", status: "pending"}
  ]}

Best Practices

🏗️ Workflow Organization

1. Use Reusable Workflows
yaml
# .github/workflows/reusable-swarm.yml
name: Reusable Swarm Workflow
on:
  workflow_call:
    inputs:
      topology:
        required: true
        type: string

jobs:
  swarm-task:
    runs-on: ubuntu-latest
    steps:
      - name: Initialize Swarm
        run: |
          npx ruv-swarm init --topology ${{ inputs.topology }}
2. Implement Proper Caching
yaml
- name: Cache Swarm Dependencies
  uses: actions/cache@v3
  with:
    path: ~/.npm
    key: ${{ runner.os }}-swarm-${{ hashFiles('**/package-lock.json') }}
3. Set Appropriate Timeouts
yaml
jobs:
  swarm-task:
    timeout-minutes: 30
    steps:
      - name: Swarm Operation
        timeout-minutes: 10
4. Use Workflow Dependencies
yaml
jobs:
  setup:
    runs-on: ubuntu-latest

  test:
    needs: setup
    runs-on: ubuntu-latest

  deploy:
    needs: [setup, test]
    runs-on: ubuntu-latest

🔒 Security Best Practices

1. Store Configurations Securely
yaml
- name: Setup Swarm
  env:
    SWARM_CONFIG: ${{ secrets.SWARM_CONFIG }}
    API_KEY: ${{ secrets.API_KEY }}
  run: |
    npx ruv-swarm init --config "$SWARM_CONFIG"
2. Use OIDC Authentication
yaml
permissions:
  id-token: write
  contents: read

- name: Configure AWS Credentials
  uses: aws-actions/configure-aws-credentials@v2
  with:
    role-to-assume: arn:aws:iam::123456789012:role/GitHubAction
    aws-region: us-east-1
3. Implement Least-Privilege
yaml
permissions:
  contents: read
  pull-requests: write
  issues: write
4. Audit Swarm Operations
yaml
- name: Audit Swarm Actions
  run: |
    npx ruv-swarm actions audit \
      --export-logs \
      --compliance-report

⚡ Performance Optimization

1. Cache Swarm Dependencies
yaml
- uses: actions/cache@v3
  with:
    path: |
      ~/.npm
      node_modules
    key: ${{ runner.os }}-swarm-${{ hashFiles('**/package-lock.json') }}
2. Use Appropriate Runner Sizes
yaml
jobs:
  heavy-task:
    runs-on: ubuntu-latest-4-cores
    steps:
      - name: Intensive Swarm Operation
3. Implement Early Termination
yaml
- name: Quick Fail Check
  run: |
    if ! npx ruv-swarm actions pre-check; then
      echo "Pre-check failed, terminating early"
      exit 1
    fi
4. Optimize Parallel Execution
yaml
strategy:
  matrix:
    include:
      - runner: ubuntu-latest
        task: test
      - runner: ubuntu-latest
        task: lint
      - runner: ubuntu-latest
        task: security
  max-parallel: 3

Debugging & Troubleshooting

🐛 Debug Tools

Debug Mode
yaml
- name: Debug Swarm
  run: |
    npx ruv-swarm actions debug \
      --verbose \
      --trace-agents \
      --export-logs
  env:
    ACTIONS_STEP_DEBUG: true
Performance Profiling
bash
# Profile workflow performance
npx ruv-swarm actions profile \
  --workflow "ci.yml" \
  --identify-slow-steps \
  --suggest-optimizations
Failure Analysis
bash
# Analyze failed runs
gh run view <run-id> --json jobs,conclusion | \
  npx ruv-swarm actions analyze-failure \
    --suggest-fixes \
    --auto-retry-flaky
Log Analysis
bash
# Download and analyze logs
gh run download <run-id>
npx ruv-swarm actions analyze-logs \
  --directory ./logs \
  --identify-errors

Real-World Examples

🚀 Complete Workflows

Example 1: Full-Stack Application CI/CD
yaml
name: Full-Stack CI/CD with Swarms
on:
  push:
    branches: [main, develop]
  pull_request:

jobs:
  initialize:
    runs-on: ubuntu-latest
    outputs:
      swarm-id: ${{ steps.init.outputs.swarm-id }}
    steps:
      - id: init
        run: |
          SWARM_ID=$(npx ruv-swarm init --topology mesh --output json | jq -r '.id')
          echo "swarm-id=${SWARM_ID}" >> $GITHUB_OUTPUT

  backend:
    needs: initialize
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Backend Tests
        run: |
          npx ruv-swarm agents spawn --type tester \
            --task "Run backend test suite" \
            --swarm-id ${{ needs.initialize.outputs.swarm-id }}

  frontend:
    needs: initialize
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Frontend Tests
        run: |
          npx ruv-swarm agents spawn --type tester \
            --task "Run frontend test suite" \
            --swarm-id ${{ needs.initialize.outputs.swarm-id }}

  security:
    needs: initialize
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Security Scan
        run: |
          npx ruv-swarm agents spawn --type security \
            --task "Security audit" \
            --swarm-id ${{ needs.initialize.outputs.swarm-id }}

  deploy:
    needs: [backend, frontend, security]
    if: github.ref == 'refs/heads/main'
    runs-on: ubuntu-latest
    steps:
      - name: Deploy
        run: |
          npx ruv-swarm actions deploy \
            --strategy progressive \
            --swarm-id ${{ needs.initialize.outputs.swarm-id }}
Example 2: Monorepo Management
yaml
name: Monorepo Coordination
on: push

jobs:
  detect-changes:
    runs-on: ubuntu-latest
    outputs:
      packages: ${{ steps.detect.outputs.packages }}
    steps:
      - uses: actions/checkout@v3
        with:
          fetch-depth: 0

      - id: detect
        run: |
          PACKAGES=$(npx ruv-swarm actions detect-changes \
            --monorepo \
            --output json)
          echo "packages=${PACKAGES}" >> $GITHUB_OUTPUT

  build-packages:
    needs: detect-changes
    runs-on: ubuntu-latest
    strategy:
      matrix:
        package: ${{ fromJson(needs.detect-changes.outputs.packages) }}
    steps:
      - name: Build Package
        run: |
          npx ruv-swarm actions build \
            --package ${{ matrix.package }} \
            --parallel-deps
Example 3: Multi-Repo Synchronization
bash
# Synchronize multiple repositories
npx claude-flow@alpha github sync-coordinator \
  "Synchronize version updates across:
   - github.com/org/repo-a
   - github.com/org/repo-b
   - github.com/org/repo-c

   Update dependencies, align versions, create PRs"

Command Reference

📚 Quick Command Guide

Workflow Generation
bash
npx ruv-swarm actions generate-workflow [options]
  --analyze-codebase       Analyze repository structure
  --detect-languages       Detect programming languages
  --create-optimal-pipeline Generate optimized workflow
Optimization
bash
npx ruv-swarm actions optimize [options]
  --workflow <path>        Path to workflow file
  --suggest-parallelization Suggest parallel execution
  --reduce-redundancy      Remove redundant steps
  --estimate-savings       Estimate time/cost savings
Analysis
bash
npx ruv-swarm actions analyze [options]
  --commit <sha>           Analyze specific commit
  --suggest-tests          Suggest test improvements
  --optimize-pipeline      Optimize pipeline structure
Testing
bash
npx ruv-swarm actions smart-test [options]
  --changed-files <files>  Files that changed
  --impact-analysis        Analyze test impact
  --parallel-safe          Only parallel-safe tests
Security
bash
npx ruv-swarm actions security [options]
  --deep-scan             Deep security analysis
  --format <format>       Output format (json/text)
  --create-issues         Auto-create GitHub issues
Deployment
bash
npx ruv-swarm actions deploy [options]
  --strategy <type>       Deployment strategy
  --risk <level>          Risk assessment level
  --auto-execute          Execute automatically
Monitoring
bash
npx ruv-swarm actions analytics [options]
  --workflow <name>       Workflow to analyze
  --period <duration>     Analysis period
  --identify-bottlenecks  Find bottlenecks
  --suggest-improvements  Improvement suggestions

Integration Checklist

✅ Setup Verification

  • GitHub CLI (gh) installed and authenticated
  • Git configured with user credentials
  • Node.js v16+ installed
  • claude-flow@alpha package available
  • Repository has .github/workflows directory
  • GitHub Actions enabled on repository
  • Necessary secrets configured
  • Runner permissions verified
Quick Setup Script
bash
#!/bin/bash
# setup-github-automation.sh

# Install dependencies
npm install -g claude-flow@alpha

# Verify GitHub CLI
gh auth status || gh auth login

# Create workflow directory
mkdir -p .github/workflows

# Generate initial workflow
npx ruv-swarm actions generate-workflow \
  --analyze-codebase \
  --create-optimal-pipeline > .github/workflows/ci.yml

echo "✅ GitHub workflow automation setup complete"

Related Skills

  • github-pr-enhancement - Advanced PR management
  • release-coordination - Release automation
  • swarm-coordination - Multi-agent orchestration
  • ci-cd-optimization - Pipeline optimization

Support & Documentation

Version History

  • v1.0.0 (2025-01-19): Initial skill consolidation
    • Merged workflow-automation.md (441 lines)
    • Merged github-modes.md (146 lines)
    • Added progressive disclosure
    • Enhanced with swarm coordination patterns
    • Added comprehensive examples and best practices

Skill Status: ✅ Production Ready Last Updated: 2025-01-19 Maintainer: claude-flow team

Frequently asked questions

What does the Github Workflow Automation AI skill do?

Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management

Why use Github Workflow Automation on TypingMind?

Because you install it once and use it with any model. Github Workflow Automation is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Github Workflow Automation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ruvnet/RuView/tree/main/.claude/skills/github-workflow-automation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Github Workflow Automation?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Github Workflow Automation?

As many as you like. As long as a model supports skills, you can use Github Workflow Automation with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Github Workflow Automation AI skill free?

Yes. It is published on GitHub by ruvnet under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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