🧠 code-contextify

Transform your entire codebase into AI-ready context in seconds


> "Turn thousands of files into one perfect prompt for your AI assistant"

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🚀 Why code-contextify?

Fed up with copying and pasting files into ChatGPT? Struggling to give Claude the full picture of your project? code-contextify solves this by creating a single, comprehensive text file containing your entire project structure and content - perfectly formatted for AI consumption.

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- 🤖 LLM Prompting - Give AI assistants complete project context
- 📚 Documentation - Generate instant project overviews
- 🔍 Code Reviews - Share full context with teammates
- 📊 Project Analysis - Understand complex codebases quickly
- 🎯 Debugging - Let AI analyze your entire codebase at once

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🎯 Quick Start

``bash


Install globally

npm install -g code-contextify

Navigate to your project folder and run:

code-contextify

Or, to analyze a different directory:

code-contextify /path/to/your/project

That's it! Your context file is ready 🎉

`

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🛠️ Installation

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- Node.js >= 14.0.0

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`bash


Global installation (recommended)

npm install -g code-contextify

Or use npx without installing

npx code-contextify /path/to/project
`

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🎮 Usage Guide

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`bash

Convert current directory

code-contextify

Convert specific directory

code-contextify /path/to/your/project

Custom output filename in current directory

code-contextify my-project-context.txt
`

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`bash

Exclude specific folders from the current directory

code-contextify --filter "node_modules,dist,build"

Exclude files with specific patterns

code-contextify --filter "test,__mocks__,*.spec.js"

Complex filtering with paths

code-contextify --filter "src/tests,docs,temp,*.log"
`

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#### 1. Prepare for AI Code Review
`bash
code-contextify review-context.txt --filter "node_modules,dist,*.min.js"
`

#### 2. Share Project Context with Team
`bash
code-contextify /path/to/project team-brief.txt
`

#### 3. Create Documentation Context
`bash
code-contextify docs-context.txt --filter "tests,__tests__,.test."
`

#### 4. Debug with AI Assistant
`bash
code-contextify debug-context.txt --filter "node_modules,*.log,temp"
`

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📋 What's In The Output?

Your generated context file includes:

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`
Project Statistics:
Total Files: 42
Total Size: 1.25 MB

`

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`
Folder Structure (Tree)
=====================
Legend: ✗ = Excluded
├── src/
│ ├── components/
│ │ ├── Header.js
│ │ └── Footer.js
│ └── utils/
├── node_modules/ ✗
├── package-lock.json (123.45 KB) ✗
└── README.md (2.34 KB)
`

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`
src/components/Header.js
------------------------
import React from 'react';
// ... actual file content
`

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🧠 AI Prompting Tips

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`
Here's the complete context of my project.
Please help me [your specific request]:

[Generated context content here]
`

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- "Explain this codebase to me"
- "Find potential bugs in this project"
- "Suggest improvements to this architecture"
- "Write documentation for this project"
- "Help me understand how these components work together"

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⚙️ How It Works

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✅ Automatically Excludes:
- Binary files (images, executables, etc.)
- Configuration files (package-lock.json, .env)
- Common directories (node_modules, .git)
- Git-ignored files and patterns
- Media files (videos, audio, etc.)

✅ Intelligently Includes:
- Source code files
- Documentation
- Configuration files you actually need
- Text-based assets

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Automatically identifies:
- JavaScript/TypeScript
- React/Vue/Angular
- Python
- And many more!

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🎯 Pro Tips

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`bash

For models with smaller context windows

code-contextify --filter "tests,docs,examples,*.md"

For models with large context windows

code-contextify # Include everything!
`

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`bash

Timestamped context files

code-contextify project_$(date +%Y%m%d_%H%M%S).txt
`

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`bash

Only include source code

code-contextify --filter "tests,docs,.md,.json,*.yml"

Only include tests

code-contextify tests-context.txt --filter "src,docs,*.md"
`

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🛡️ Security & Privacy

- Local Processing - Your code never leaves your machine
- Respects .gitignore - Doesn't include ignored files
- No Telemetry - Zero data collection
- Open Source - Audit the code yourself

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🤝 Contributing

Contributions welcome! Here's how to get started:

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

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- 🌍 Language detection improvements
- 🎨 Better output formatting
- ⚡ Performance optimizations
- 📚 More examples and documentation
- 🧪 Test coverage

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📄 License

This project is licensed under MIT with Commons Clause - see the LICENSE file for details.

Commercial use requires permission.

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👨‍💻 Author

Nidal Siddique Oritro
- Website: iam.ioritro.com
- GitHub: @ElvinEga

Built with ❤️ for developers working with AI

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🆘 Support

Need help?

- 🐛 Report an issue
- 💬 Join discussions
- 📧 Contact the author

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🌟 Show Your Support

If this tool saves you time:
- ⭐ Star this repository
- 🐦 Tweet about it
- 🤝 Recommend to fellow developers
- 💖 Sponsor the project

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"Turn your codebase into conversation - one context file at a time"