AI Developer Workflow Collection

🚀 Enterprise-grade AI-powered workflows for automating software development processes, from requirements to deployment.

English | ภาษาไทย

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📋 Table of Contents

• Overview
• Key Features
• Workflow Systems
• Quick Start
• Integration with Existing Projects
• Architecture
• Available Skills
• Command Reference
• Prerequisites
• Installation
• Usage Examples
• Contributing
• License

🎯 Overview

The AI Developer Workflow Collection is a comprehensive suite of markdown-based workflows designed to revolutionize how development teams work with AI assistants. These workflows provide structured, repeatable processes for common development tasks, ensuring consistency, quality, and efficiency across your entire development lifecycle.

Why Use These Workflows?

• 🤖 AI-First Design: Built specifically for AI assistants like Claude, ChatGPT, and Cursor
• 📊 Structured Processes: Transform ad-hoc development into systematic, repeatable workflows
• 🔍 Multi-Perspective Reviews: Get comprehensive code analysis from specialized reviewers
• 👥 Team Scalability: Perfect for onboarding junior developers and maintaining standards
• 🔄 GitLab Integration: Seamless integration with your existing development pipeline

✨ Key Features

Core Capabilities

Feature	Description	Benefit
PRD Generation	Interactive requirements gathering with AI	Clear, unambiguous specifications
Task Decomposition	Automatic breakdown of PRDs into tasks	Manageable, trackable work items
Multi-Specialist Review	5 specialized reviewers for different aspects	Comprehensive quality assurance
GitLab Automation	Direct integration with issues and MRs	Streamlined workflow management
Educational Feedback	Mentoring through code reviews	Team skill development
Bilingual Support	Full English and Thai documentation	Global team accessibility

🔧 Workflow Systems

1. PRD-Driven Workflow

Transform ideas into implementation through structured requirements:

graph LR
    A[Idea] --> B[Create PRD]
    B --> C[Generate Tasks]
    C --> D[Process Tasks]
    D --> E[Implementation]

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Components:

• 01-create-prd.md - Interactive PRD creation with clarifying questions
• 02-generate-tasks.md - Automatic task generation from PRDs
• 03-process-task-list.md - Task execution and management

Key Benefits:

• Reduces ambiguity in requirements
• Creates actionable, developer-friendly tasks
• Maintains traceability from idea to implementation

2. Review-Driven Workflow

Comprehensive code review system with specialized analysis:

graph TD
    A[Code Changes] --> B[Branch Review]
    B --> C{Specialist Reviewers}
    C --> D[Code Quality]
    C --> E[Security]
    C --> F[Performance]
    C --> G[API Design]
    C --> H[Education]
    D --> I[Comprehensive Report]
    E --> I
    F --> I
    G --> I
    H --> I
    I --> J[GitLab Feedback]

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Specialist Reviewers:

Reviewer	Focus Area	Auto-Applies To
code-reviewer	General quality, patterns, maintainability	All code files
security-reviewer	Vulnerabilities, OWASP compliance	Security-sensitive files
performance-reviewer	Bottlenecks, optimization opportunities	All code files
api-reviewer	RESTful design, consistency	API endpoints
mr-reviewer	Educational feedback, mentoring	Manual invocation

🚀 Quick Start

Basic Usage

# 1. Create a new PRD for your feature
# Use the PRD workflow guide with your AI assistant

# 2. Extract GitLab issues for review
@extract-issues

# 3. Review a specific issue implementation
@branch-review #123

# 4. Run comprehensive review with GitLab posting
@branch-review #123 --post

Focused Reviews

# Security-focused review
@branch-review feature/authentication --security-focus

# Performance optimization review
@branch-review feature/data-processing --performance-focus

# API design review
@branch-review feature/rest-api --api-focus

# Educational review for junior developers
@mr-reviewer https://gitlab.com/project/merge_requests/45

🔗 Integration with Existing Projects

Using Git Subtree (Recommended)

Add these workflows directly to your existing codebase using git subtree. This approach allows you to:

• Keep workflows versioned with your code
• Customize workflows for your specific needs
• Share improvements back to the community
• Avoid submodule complexity

Adding Workflows to Your Project

# Add as a hidden directory in your project root
git subtree add --prefix=.ai-workflows \
  https://github.com/tkhongsap/ai-dev-workflow.git main --squash

# Or add to a specific tools directory
git subtree add --prefix=tools/ai-workflows \
  https://github.com/tkhongsap/ai-dev-workflow.git main --squash

# For a more integrated approach, add to your docs
git subtree add --prefix=docs/ai-workflows \
  https://github.com/tkhongsap/ai-dev-workflow.git main --squash

Updating Workflows

# Pull latest improvements from upstream
git subtree pull --prefix=.ai-workflows \
  https://github.com/tkhongsap/ai-dev-workflow.git main --squash

# This will merge updates while preserving your customizations

Contributing Improvements Back

# Create a feature branch for your improvements
git subtree push --prefix=.ai-workflows \
  https://github.com/tkhongsap/ai-dev-workflow.git feature/your-improvement

# Then create a pull request from the feature branch

Best Practices for Subtree Integration

1. Choose the Right Location:

   • .ai-workflows/ - Hidden, doesn't clutter project root
   • tools/workflows/ - Grouped with other development tools
   • docs/workflows/ - Part of documentation structure

2. Customize for Your Project:

   • Modify MDC rules to match your coding standards
   • Add project-specific review criteria
   • Create custom workflow variants

3. Document the Integration:

   # In your project's README.md
   ## AI Workflows
   This project includes AI-powered development workflows in `.ai-workflows/`.
   See `.ai-workflows/README.md` for usage instructions.

4. Team Onboarding:

   • Include workflow usage in onboarding docs
   • Create project-specific examples
   • Set up GitLab environment variables

Alternative: Git Submodule

For teams preferring submodules:

# Add as submodule
git submodule add https://github.com/tkhongsap/ai-dev-workflow.git .ai-workflows

# Initialize and update
git submodule update --init --recursive

🏗️ Architecture

Directory Structure

ai-dev-workflow/
├── .claude/
│   ├── commands/                   # Slash commands
│   ├── agents/                     # Custom agents
│   └── skills/                     # Reusable skills
│       └── english-to-thai-cultural-translation.md
├── prd-driven-workflow/
│   ├── 01-create-prd.md           # PRD creation guide
│   ├── 02-generate-tasks.md       # Task generation
│   ├── 03-process-task-list.md    # Task processing
│   └── *-replit.md                # Replit variants
├── review-driven-workflow/
│   ├── review-workflow.mdc        # Main orchestrator
│   ├── extract-issues.mdc         # GitLab integration
│   ├── branch-review.mdc          # Branch analysis
│   ├── code-reviewer.mdc          # Code quality
│   ├── security-reviewer.mdc      # Security analysis
│   ├── performance-reviewer.mdc   # Performance optimization
│   ├── api-reviewer.mdc           # API design
│   └── mr-reviewer.mdc            # Educational reviews
└── CLAUDE.md                       # AI assistant instructions

File Types

Extension	Purpose	Format
.md	Workflow documentation	Standard Markdown
.mdc	Review rules with automation	Markdown + Front Matter
.claude/skills/*.md	Reusable AI skills	Markdown + YAML Front Matter

MDC Rule Structure

---
description: "Rule description"
globs: ["**/*.py", "**/*.js"]  # Auto-apply patterns
alwaysApply: true               # Apply to all files
---
# Rule content and review criteria

Skill File Structure

Skills are reusable capabilities that can be invoked during conversations. They use YAML front matter for metadata:

---
name: skill-name
description: Brief description of when to use this skill
---

# Skill Title

Detailed instructions for the AI assistant on how to execute this skill.

🎨 Available Skills

English to Thai Cultural Translation

Skill Name: english-to-thai-cultural-translation

Purpose: Provides culturally-aware translation from English to Thai, ensuring natural phrasing and appropriate formality levels.

Key Features:

• Formality level selection (กระผม/ผม/ครับ/ค่ะ/นะ)
• Cultural idiom adaptation
• Context-appropriate honorifics and pronouns
• Natural Thai phrasing (avoiding literal translations)
• Technical term handling
• Buddhist era date conversion

When to Use:

• Translating documentation to Thai
• Adapting English content for Thai audiences
• Questions about Thai language formality
• Localizing technical content for Thailand
• Understanding Thai pronouns and particles

Example Usage:

User: "Translate this README to Thai with professional formality"
Assistant: [Uses english-to-thai-cultural-translation skill]

File Location: .claude/skills/english-to-thai-cultural-translation.md

📊 Command Reference

Workflow Commands

Command	Description	Example
@extract-issues	Extract GitLab issues	@extract-issues
@branch-review	Review branch/issue	@branch-review #123
@code-reviewer	Code quality review	Auto-invoked
@security-reviewer	Security analysis	Auto-invoked
@performance-reviewer	Performance review	Auto-invoked
@api-reviewer	API design review	Auto-invoked
@mr-reviewer	Educational review	@mr-reviewer <url>

Command Options

Option	Description	Usage
--post	Post to GitLab	@branch-review #123 --post
--security-focus	Security emphasis	@branch-review #123 --security-focus
--performance-focus	Performance emphasis	@branch-review #123 --performance-focus
--api-focus	API design emphasis	@branch-review #123 --api-focus
--queue	Process review queue	@branch-review --queue

📋 Prerequisites

Required

• Git repository
• AI assistant (Claude, ChatGPT, Cursor, etc.)
• Markdown viewer/editor

Optional (for GitLab Integration)

• GitLab account with API access
• Environment variables:

  export GITLAB_ACCESS_TOKEN="your_token"
  export GITLAB_PROJECT_ID="your_project_id"
  export GITLAB_URL="https://gitlab.yourdomain.com"  # Optional

💾 Installation

Standard Installation

# Clone from GitHub
git clone https://github.com/tkhongsap/ai-dev-workflow.git

# Or clone from GitLab (internal)
git clone https://gitlab.thaibevapp.com/thaibev-ai/ai-dev-tools-workflows/ai-dev-tasks.git ai-dev-workflow

# Navigate to the directory
cd ai-dev-workflow

# Set up GitLab integration (optional)
cp .env.example .env
# Edit .env with your GitLab credentials

Integration Installation

See Integration with Existing Projects section above.

📚 Usage Examples

Example 1: Creating a New Feature

# 1. Start with PRD creation
# Tell your AI: "I need to create a PRD for a user authentication feature"
# AI will use 01-create-prd.md to guide you

# 2. Generate tasks from PRD
# Tell your AI: "Generate tasks from prd-authentication.md"
# AI will create a structured task list

# 3. Process tasks
# Tell your AI: "Let's work through the authentication tasks"
# AI will systematically complete each task

Example 2: Reviewing a Feature Branch

# 1. Extract current issues
@extract-issues

# 2. Review specific implementation
@branch-review #456 --post

# 3. Check the generated review
cat workflow/review-456-2024-01-15.md

Example 3: Mentoring Junior Developers

# 1. Junior developer creates MR
# 2. Run educational review
@mr-reviewer https://gitlab.com/project/merge_requests/789

# 3. Review provides:
# - Detailed explanations
# - Best practice suggestions
# - Learning resources
# - Positive reinforcement

🤝 Contributing

We welcome contributions! Here's how you can help:

Ways to Contribute

1. New Workflows: Create new workflow patterns
2. Workflow Improvements: Enhance existing workflows
3. Documentation: Improve documentation and examples
4. Translations: Add new language support
5. Integration Tools: Build integration scripts

Contribution Process

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Contribution Guidelines

• Follow existing markdown formatting
• Include examples in documentation
• Test workflows with multiple AI assistants
• Update both English and Thai documentation if applicable
• Add yourself to CONTRIBUTORS.md

📄 License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

What This Means

✅ You CAN:

• Use commercially
• Modify and distribute
• Use privately
• Place warranty

❌ You CANNOT:

• Hold liable
• Use trademark

📋 You MUST:

• Include copyright
• Include license
• State changes
• Include NOTICE

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🙏 Acknowledgments

• Built for the developer community
• Inspired by best practices from leading tech companies
• Designed for seamless AI assistant integration

📮 Support

• GitHub Issues: https://github.com/tkhongsap/ai-dev-workflow/issues
• GitHub Discussions: https://github.com/tkhongsap/ai-dev-workflow/discussions
• GitLab Repository: https://gitlab.thaibevapp.com/thaibev-ai/ai-dev-tools-workflows/ai-dev-tasks

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Built with ❤️ for developers who believe in the power of AI-assisted development

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