AFKmate 🤖

Your AFK coding companion — AI-powered code analysis while you're away.

AFKmate is a Visual Studio Code extension that automatically analyzes your code after 3 minutes of inactivity, identifying structural issues, syntax errors, and potential bugs without requiring manual intervention.

✨ Features

💤 AFK-Powered Analysis

• Idle Detection: Automatically triggers analysis after 3 minutes of AFK time
• Smart File Tracking: Only analyzes files marked as "modified" in VS Code
• Zero Manual Debugging: Work on your code, go AFK, come back to insights

🎯 Comprehensive Error Detection

• Syntax Errors: Catches typos, missing semicolons, and language-specific syntax issues
• Structural Problems: Identifies architectural issues and code smell
• Logic Errors: Detects potential bugs that require debugging
• Style Issues: Suggests improvements for code readability and best practices

💡 Intelligent UI

• Side Panel Interface: Clean panel in your activity bar
• One-Click Analysis: "Analyze Now" button for instant feedback
• Clickable Issues: Jump directly to error locations with one click
• Categorized Results: Errors, warnings, and suggestions clearly organized
• Real-time Updates: See analysis progress and results instantly

🔌 LLM-Powered Backend

• Integrated with Vercel-deployed backend API
• Supports multiple LLM providers (OpenAI, Claude, Gemini)
• Configurable API endpoint and authentication
• Real-time analysis with 30-second timeout handling

📦 Installation

From Source (Development)

1. Clone the repository: git clone https://github.com/tu-tu-op/afkmate.git

2. Install dependencies: npm install

3. Compile the extension: npm run compile

4. Press F5 to run in Extension Development Host

From VSIX (Coming Soon)

Download the .vsix file and install via: code --install-extension afkmate-0.0.1.vsix

🚀 Usage

Automatic Analysis

1. Open any project in VS Code
2. Start editing files
3. Go AFK for 3 minutes (grab coffee ☕)
4. Come back to automatic analysis results in the AFKmate panel

Manual Analysis

• "Analyze Now" Button: Click the button in the AFKmate sidebar panel
• Command Palette (Ctrl+Shift+P / Cmd+Shift+P):
  • AFKmate: Analyze Now - Trigger immediate analysis

Keyboard Shortcuts

You can customize keyboard shortcuts in VS Code settings:

• Open Command Palette → Preferences: Open Keyboard Shortcuts
• Search for "AFKmate"

⚙️ Configuration

Access settings via File → Preferences → Settings and search for "AFKmate":

Example Settings

{ "afkmate.idleTimeMinutes": 5, "afkmate.autoStart": true, "afkmate.apiUrl": "https://your-backend.vercel.app/api/analyze", "afkmate.apiKey": "your-api-key-here" }

🏗️ Architecture

Project Structure

afkmate/ ├── src/ │ ├── extension.ts # Main extension entry point │ ├── idleDetector.ts # Idle time detection logic │ ├── fileTracker.ts # Modified files tracker │ ├── analyzer.ts # Code analysis engine with LLM integration │ └── webview/ │ └── webviewViewProvider.ts # Panel UI provider ├── package.json # Extension manifest └── tsconfig.json # TypeScript configuration

Key Components

1. Idle Detector

Monitors editor activity and triggers analysis after configured idle time:

• Tracks text changes, editor switches, and cursor movements
• Configurable idle threshold (default: 3 minutes)
• Automatic reset on any user activity

2. File Tracker

Maintains a list of modified files using VS Code's workspace API:

• Listens to onDidChangeTextDocument events
• Tracks saved and unsaved changes
• Integrates with source control status

3. Code Analyzer

Core analysis engine with LLM integration:

• Collects VS Code's built-in diagnostics
• Connects to Vercel-deployed backend API
• Handles JSON parsing with markdown code block removal
• Returns structured error, warning, and suggestion data

4. Webview Panel

Custom UI displaying analysis results:

• Activity bar integration with AFKmate icon
• Interactive "Analyze Now" button
• Issue list with file navigation
• Real-time status updates

🔌 Backend Integration

AFKmate uses a Vercel-deployed backend for LLM-powered analysis.

Current Backend

• URL: https://ecospace-backend.vercel.app/api/analyze
• Method: POST
• Timeout: 30 seconds

API Contract

Request Format:

{ "input": "file content here", "fileName": "App.tsx", "language": "typescript", "analysisTypes": ["syntax", "structure", "logic", "style"] }

Response Format:

{ "result": { "errors": [ { "line": 10, "column": 5, "severity": "error", "message": "Missing semicolon", "type": "syntax" } ], "warnings": [...], "suggestions": [...] } }

Custom Backend Setup

To use your own backend:

1. Deploy your LLM analysis API
2. Update afkmate.apiUrl in VS Code settings
3. Optionally set afkmate.apiKey for authentication

🛠️ Development

Prerequisites

• Node.js (v16 or higher)
• Visual Studio Code (v1.74.0 or higher)
• TypeScript knowledge

Build Commands

Install dependencies npm install

Compile TypeScript npm run compile

Watch mode (auto-compile on changes) npm run watch

Run linter npm run lint

Debugging

1. Open project in VS Code
2. Press F5 to launch Extension Development Host
3. Set breakpoints in TypeScript files
4. View Debug Console for logs

Testing

npm test

🤝 Contributing

Contributions are welcome! Please follow these steps:

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

Code Style

• Use TypeScript with strict mode enabled
• Follow VS Code extension best practices
• Add comments for complex logic
• Maintain consistent formatting with ESLint

📝 Roadmap

• [x] LLM integration with Vercel backend
• [x] One-click "Analyze Now" button
• [ ] Multiple LLM provider support (OpenAI, Claude, Gemini)
• [ ] Customizable analysis rules
• [ ] Multi-language support enhancements
• [ ] Performance optimizations for large files
• [ ] Diff-based analysis (analyze only changed lines)
• [ ] Team sharing of analysis configurations
• [ ] Integration with CI/CD pipelines
• [ ] Custom rule creation UI

🐛 Known Issues

• Backend responses with improperly escaped JSON may show as text suggestions
• Large files (>10MB) may cause performance delays
• Line-by-line extraction fallback for complex JSON responses

Report issues on GitHub Issues

📜 License

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

👤 Author

Sushant Singh

• GitHub: @tu-tu-op
• Project: AFKmate

🙏 Acknowledgments

• Inspired by automated code analysis tools
• Built with VS Code Extension API
• Backend deployed on Vercel
• LLM-powered analysis

📚 Resources

• VS Code Extension Documentation
• Extension API Reference
• Webview Guide

Made with ❤️ for developers who code better when they're AFK

If you find this extension helpful, please ⭐ star the repository!