AI-Powered Development

AI Workflow Resources

Structured knowledge graphs and JSON resources enabling LLM-powered development assistance. Perfect for GitHub Copilot, Cursor AI, and other AI coding tools.

AI-Ready Knowledge Resources

Structured Data for LLM Integration

These AI Workflow Resources provide structured JSON knowledge graphs and workflow definitions that enable LLMs (Large Language Models) to understand the codebase architecture and provide intelligent assistance. Generated from the comprehensive analysis, these resources are ready for integration with AI coding assistants.

📚 Knowledge Graphs

Structured JSON representations of codebase architecture for AI context

🔄 AI Workflows

Predefined development workflows optimized for AI pair programming

⚙️ Configurations

System prompts and configurations for consistent AI assistance

Knowledge Graphs

JSON-formatted knowledge graphs provide AI assistants with deep contextual understanding of the codebase architecture.

JSON

Main Knowledge Graph

Comprehensive unified graph combining all architectural knowledge, components, and relationships.

Complete System Download →
CORE

User Authentication Cluster

Authentication system components, OAuth providers, and session management.

Cluster-Specific Download →
LEARN

Quiz Assessment Cluster

Quiz service components, question types, grading logic, and submission flow.

Cluster-Specific Download →
View All

All Cluster Graphs

Browse all cluster-specific knowledge graphs organized by category.

All Clusters View All →

AI Workflows

Predefined workflows help AI assistants understand common development tasks and generate better code.

Workflow

Feature Development

  1. Analyze feature requirements
  2. Identify affected components
  3. Generate service objects and models
  4. Create controllers and views
  5. Write RSpec tests
  6. Update documentation
View Workflow →
Workflow

Microservice Integration

  1. Define API contract
  2. Create ACFS resource models
  3. Implement service client
  4. Add error handling
  5. Write integration tests
  6. Update service documentation
View Workflow →
Workflow

Bug Investigation

  1. Analyze error logs and stack traces
  2. Identify affected components
  3. Review recent changes
  4. Propose fix with tests
  5. Verify no regressions
  6. Update error handling
View Workflow →
Workflow

Refactoring

  1. Identify code smells
  2. Analyze dependencies
  3. Propose refactoring strategy
  4. Implement changes incrementally
  5. Ensure test coverage
  6. Update documentation
View Workflow →

Integration Guides

GitHub Copilot

Use IDP resources with GitHub Copilot for context-aware code suggestions.

1. Open workspace in VS Code

2. Load knowledge graph JSON

3. Use @workspace in Copilot Chat

4. Reference cluster reports

View Full Guide

Cursor AI

Integrate IDP knowledge into Cursor's AI-powered development environment.

1. Import knowledge graphs

2. Configure .cursorrules

3. Add cluster report context

4. Use Composer mode

View Full Guide

Best Practices

💡 Context Loading

  • → Load relevant knowledge graph before starting
  • → Include cluster reports for affected components
  • → Reference architecture diagrams
  • → Keep context focused and relevant

🎯 Workflow Selection

  • → Choose workflow matching your task
  • → Follow workflow steps sequentially
  • → Validate each step before proceeding
  • → Adapt workflow to specific needs

✅ Quality Checks

  • → Review AI-generated code carefully
  • → Run tests before committing
  • → Verify architectural patterns
  • → Update documentation as needed

Explore More Resources

Dive deeper into the architecture and component details through our comprehensive documentation.

Architecture Overview Cluster Reports Knowledge Graph