Quick Setup in 5 Minutes

Get started with CSVLOD-AI Framework for AI-native development. Set up context management and MCP tools for efficient AI workflows.

🚀 Production Ready 📦 12 MCP Tools 🔧 Context Management 📚 Open Source
1

Clone CSVLOD-AI Framework

Download the complete CSVLOD-AI framework with all tools and documentation.

Repository Setup
# Clone the framework repository git clone https://github.com/hamzaamjad/csvlod-ai-framework.git # Navigate to framework directory cd csvlod-ai-framework # Verify repository structure ls -la # Check framework status echo "✅ CSVLOD-AI Framework Ready"

📦 Framework Components: You now have access to 12 MCP tools, context management system, and comprehensive documentation for AI-native development.

2

Install MCP Server

Set up the Model Context Protocol server for AI integration and install dependencies.

MCP Server Installation
# Navigate to MCP server directory cd mcp-server # Install dependencies npm install # Build the MCP server npm run build # Verify installation npm test

✅ Expected Result: 100% framework health score with all revolutionary v3.0 capabilities operational including Context Intelligence Engine and Multimodal Processor.

3

Explore CSVLOD Structure

Familiarize yourself with the six CSVLOD categories that structure all enterprise knowledge.

📋 Considerations

Framework principles and business guidelines

.context/principles/

⚙️ Standards

Technical standards and quality requirements

.context/standards/

🔮 Visions

Strategic direction and evolution goals

.context/vision/

🗺️ Landscapes

Component inventory and integration maps

.context/landscape/

📊 Outlines

Development initiatives and coordination

.context/initiatives/

🏗️ Designs

Technical specifications and architecture

.context/designs/
Explore CSVLOD
# Explore the context structure find .context -name "*.md" | head -10 # Read the framework principles cat .context/principles/framework-principles.md # Check current initiatives ls .context/initiatives/active/
4

Try the AI Tools

Explore the comprehensive suite of AI-native tools designed for framework operations.

🔍 Validation Scripts

  • • Framework compliance checking
  • • Context structure validation
  • • Link integrity verification
  • • Prompt structure analysis

⚡ Quick Prompts

  • • Rapid context loading
  • • Validation workflows
  • • Improvement scanning
  • • Pattern discovery

📖 Live Examples

  • • Context loading workflows
  • • Task execution patterns
  • • Parallel operations
  • • Self-improvement cycles

🛠️ Utility Tools

  • • Context quality analysis
  • • Project quick-start
  • • Prompt generation
  • • Metrics collection
AI Tools Demo
# Quick context loading (for AI agents) cat .ai/prompts/quick-context.md # Generate a new project python .ai/tools/quick-start.py --init-repo my-new-project # Analyze framework quality python .ai/tools/context-analyzer.py . --detailed # Generate custom prompts python .ai/tools/prompt-generator.py --template execution --domain "web development"
5

Start Your First Project

Use the framework's quick-start tool to create your first AI-native project with complete CSVLOD structure.

New Project Setup
# Create a new project with CSVLOD structure python .ai/tools/quick-start.py --full-setup ../my-ai-project # Or initialize in existing directory python .ai/tools/quick-start.py --init-repo . # Validate your new setup python .ai/validations/csvlod-compliance.py ../my-ai-project

What You Get:

  • ✅ Complete CSVLOD directory structure
  • ✅ Customized AI-CONTEXT.md for your project
  • ✅ Working AGENT-MANIFEST.yaml configuration
  • ✅ All validation tools and utilities
  • ✅ Ready-to-use prompts and examples
  • ✅ Git repository with initial commit

You're Ready to Build!

You now have a complete CSVLOD-AI Framework implementation. Explore the documentation and examples to unlock the full potential of AI-native development.

Read Full Documentation See Live Examples Join Community

Troubleshooting

Python Dependencies

Some validation scripts require Python packages:

pip install pyyaml requests markdown beautifulsoup4 gitpython

Validation Failures

If validation scripts fail:

  • Check Python version (3.8+ required)
  • Ensure you're in the repository root directory
  • Install missing dependencies
  • Review error messages for specific issues

Getting Help

Need assistance? Here's how to get help: