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OnboardGPT

OnboardGPT

HarshalGajjar

|
15 installs
| (0) | Free
AI-powered repository analysis with structure intelligence, architectural pattern detection, and smart recommendations
Installation
Launch VS Code Quick Open (Ctrl+P), paste the following command, and press enter.
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OnboardGPT for VS Code

🚀 AI-powered codebase onboarding with Structure Intelligence - Quickly understand any project with intelligent analysis, architectural pattern detection, and smart recommendations.

Features

  • 🔍 One-Click Analysis: Run comprehensive codebase analysis with a single command
  • 📊 Rich Markdown Reports: Get detailed insights in an easy-to-read format
  • 🌐 Multi-Language Support: Works with JavaScript, Python, Java, Go, Rust, and more
  • ⚡ Real-time Progress: Visual feedback during analysis
  • 🎯 Actionable Insights: Get specific guidance on running and developing the project
  • 🧠 Structure Intelligence: AI-powered architectural pattern detection and organization analysis
  • 💡 Smart Recommendations: Get actionable suggestions for improving code organization
  • 🏗️ Pattern Recognition: Automatically detect MVC, Clean Architecture, microservices, and more
  • 🤖 AI Summaries: Generate intelligent summaries tailored to different audiences
  • 🤖 AI Agent System: Revolutionary AI agents that understand what your project actually does
  • 🎯 Project Purpose Analysis: AI explains what the project is, who uses it, and why
  • 👥 User-Focused Insights: Prioritizes what developers need to know to get started
  • 🔧 Configurable AI: Use your own HuggingFace API key for enhanced features

Getting Started

Installation

  1. Install the extension from the VS Code Marketplace
  2. Open any project folder in VS Code
  3. You're ready to analyze!

Using the Extension

  1. Open a project: File → Open Folder (select any codebase)
  2. Run analysis: Press Ctrl+Shift+P (or Cmd+Shift+P on Mac)
  3. Search for: "OnboardGPT: Onboard Codebase"
  4. View results: A new document opens with your analysis report

![Demo GIF showing the analysis in action]

What You'll Get

📊 Project Overview

  • Total file count and key files identified
  • Technology stacks and package versions
  • Entry points for running the application

🔧 Technology Detection

Automatically identifies:

  • Package Managers: npm, pip, cargo, maven, gradle
  • Frameworks: Express, React, Flask, Django, Spring Boot, and more
  • Development Tools: TypeScript, Vite, Jest, pytest, etc.

🚀 Entry Point Discovery

Finds how to run the project:

  • Web Applications: Servers, APIs, web frameworks
  • CLI Tools: Command-line utilities and scripts
  • Libraries: Modules and packages with exports

🎯 Getting Started Guide

  • Language-specific installation instructions
  • How to run detected applications
  • Suggested next steps for development

🤖 AI Understanding: What This Project Is About

🎯 Project Purpose

This is a full-stack web application that provides real-time task management and collaboration features for teams. It combines a React frontend with an Express.js backend and uses PostgreSQL for data persistence.

👥 Who Uses This

  • Development Teams: For managing sprints, tasks, and project milestones
  • Project Managers: For tracking progress and resource allocation
  • Stakeholders: For viewing project status and deliverables

⚙️ How It Works

The application uses a modern web architecture with a React SPA frontend communicating with a RESTful API backend. Real-time updates are handled through WebSocket connections, and the system includes authentication, role-based access control, and data visualization features.

💰 Business Value

Reduces project management overhead by 40% through automated task tracking, provides real-time visibility into project status, and integrates with existing development workflows to improve team productivity.

🧠 Structure Intelligence

📊 Organization Metrics

  • Structure Score: 85%
  • Directory Depth: 4 max, 2.3 avg
  • Project Type: web-application (medium scale)
  • Confidence: 90%

🏗️ Architectural Patterns

React Component Architecture (80% confidence)

  • Component-based architecture using React for building reusable UI components
  • Evidence: Found components directory, Using React framework

💡 Recommendations

✅ Excellent Repository Organization (low priority) This web-application project demonstrates excellent organizational practices...

💡 Consider Adding Integration Tests (medium priority) While unit tests are present, integration tests would improve confidence...

Example Analysis Report

# 🚀 OnboardGPT Analysis: react-express-app

## 📊 Overview
- **Total Files**: 847
- **Technology Stacks**: 1
- **Entry Points**: 2

## 🔧 Technology Stack

### TypeScript
**12 packages detected:**
- 📦 `express`: ^4.18.0
- 📦 `react`: ^18.2.0
- 📦 `prisma`: ^5.0.0
- 🔧 `vite (dev)`: ^5.0.0

## 🚀 Entry Points

### 🌐 Web Applications
- **`server/index.ts`**
  - Routes/Functions: app, listen, apiRoutes

### 📚 Libraries & Modules
- **`src/index.ts`**
  - Exports: App, components, utils

## 🧠 Structure Intelligence

### 📊 Organization Metrics
- **Structure Score**: 85%
- **Directory Depth**: 4 max, 2.3 avg
- **Project Type**: web-application (medium scale)
- **Confidence**: 90%

### 🏗️ Architectural Patterns
**React Component Architecture** (80% confidence)
- Component-based architecture using React for building reusable UI components
- Evidence: Found components directory, Using React framework

### 💡 Recommendations
✅ **Excellent Repository Organization** (low priority)
This web-application project demonstrates excellent organizational practices...

💡 **Consider Adding Integration Tests** (medium priority)
While unit tests are present, integration tests would improve confidence...

## 🎯 Getting Started

### Running the Web Application
```bash
npm install
npm run dev

Dependencies

  • Node.js: npm install or yarn install

## Supported Languages

| Language | What's Detected | Package Managers |
|----------|----------------|------------------|
| **JavaScript/TypeScript** | React, Express, Vue, Angular | npm, yarn |
| **Python** | Flask, Django, FastAPI | pip, pipenv, poetry |
| **Java** | Spring Boot, Maven projects | maven, gradle |
| **Go** | HTTP servers, CLI tools | go modules |
| **Rust** | Web frameworks, binaries | cargo |

## Extension Commands

| Command | Description | Keyboard Shortcut |
|---------|-------------|-------------------|
| `OnboardGPT: Onboard Codebase` | Analyze current workspace | `Ctrl+Shift+P` → search |

## Settings

Configure OnboardGPT through VS Code settings:

| Setting | Description | Default |
|---------|-------------|---------|
| `onboardgpt.huggingfaceToken` | HuggingFace API token for AI features | None |
| `onboardgpt.modelName` | AI model to use | `Qwen/Qwen2.5-Coder-32B-Instruct` |
| `onboardgpt.enableAISummary` | Enable AI-generated summaries | `true` |
| `onboardgpt.enableStructureIntelligence` | Enable structure intelligence analysis | `true` |
| `onboardgpt.enableAIRecommendations` | Enable AI-powered recommendations | `true` |
| `onboardgpt.enableAIAgents` | Enable AI agent system for user-focused analysis | `true` |
| `onboardgpt.agentMaxFiles` | Maximum files for AI agents to analyze | `50` |
| `onboardgpt.agentMaxDepth` | Maximum directory depth for AI agents | `5` |
| `onboardgpt.summaryAudience` | Target audience for summaries | `developer` |

### Getting a HuggingFace API Key
1. Visit [HuggingFace](https://huggingface.co/settings/tokens)
2. Create a free account
3. Generate a new API token
4. Add it to your VS Code settings
5. Enjoy enhanced AI-powered analysis!

## Troubleshooting

### No Analysis Results?
- **Check workspace**: Make sure you have a folder open (not just individual files)
- **Verify project type**: Extension works best with projects that have package files (package.json, requirements.txt, etc.)
- **Large projects**: Analysis may take a few seconds for very large codebases

### Extension Not Working?
1. **Reload VS Code**: `Ctrl+Shift+P` → "Developer: Reload Window"
2. **Check output**: View → Output → Select "OnboardGPT" from dropdown
3. **Report issues**: File a bug report on our GitHub repository

## Privacy & Data

- **Local Analysis**: All code analysis happens locally on your machine
- **No Data Sent**: Your code never leaves your computer
- **No Telemetry**: We don't collect usage data or analytics
- **Optional AI**: AI features only work if you provide your own API key
- **Secure**: API keys are stored locally in VS Code settings

## Contributing

Found a bug or want to add support for a new language?

1. Visit our [GitHub repository](https://github.com/yourusername/onboardgpt)
2. Check existing issues or create a new one
3. Submit a pull request with your improvements

## Roadmap

- 🔄 **Real-time Updates**: Watch files and update analysis automatically
- 🌐 **Web Interface**: Browser-based analysis dashboard
- 🔗 **IDE Integration**: Support for more editors beyond VS Code
- 🎨 **Custom Templates**: Create your own analysis report templates

## Release Notes

### v1.0.0
- 🎉 Initial release
- ✅ Multi-language support (JavaScript, Python, Java, Go, Rust)
- ✅ Entry point detection
- ✅ Technology stack analysis
- ✅ Rich Markdown reports

### v1.2.0
- 🧠 Structure Intelligence with AI-powered analysis
- 🏗️ Architectural pattern detection (MVC, Clean Architecture, etc.)
- 💡 Smart recommendations for code organization
- 🤖 AI-generated summaries with HuggingFace integration
- 🔧 Configurable AI settings and model selection
- 📊 Advanced organization metrics and insights

---

**Happy coding!** 🚀

*Built with ❤️ by the OnboardGPT team*
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