AI Code Review Formatter

A versatile command-line tool that prepares source code for AI-powered code review and analysis. This tool formats your codebase into markdown files optimized for AI tools like ChatGPT, Perplexity AI, and other LLM-based code analysis platforms.

Features

• Smart File Splitting: Automatically splits large codebases into optimally sized chunks for AI analysis
• Markdown Formatting: Creates well-structured markdown files with proper code highlighting
• Project Context: Preserves project structure and relationships between files
• File Statistics: Includes metadata like file size, line count, and dependencies
• Cross-Platform: Works on Linux, macOS, and other Unix-like systems
• AI Tool Optimization: Formatted output is optimized for various AI analysis tools

Installation

git clone https://github.com/sssgun/ai-code-review-formatter.git
cd ai-code-review-formatter
chmod +x prepare_code_analysis.sh

Usage

./prepare_code_analysis.sh [source_directory] [output_directory]

Arguments

• source_directory: Directory containing source files (default: current directory)
• output_directory: Directory for output files (default: current directory)

Output Format

The script generates markdown files with the following structure:

{project_name}_{index}_{timestamp}.md

Each file contains:

• Project information and structure
• File metadata (size, line count)
• Syntax-highlighted source code
• File relationships and dependencies

Why Use This Tool?

1. AI-Friendly Format: Output is specifically designed for AI code analysis tools
2. Maintains Context: Preserves project structure and file relationships
3. Size Management: Handles large codebases by intelligently splitting files
4. Documentation Ready: Generated files can also serve as project documentation

Example

# Analyze a Python project
./prepare_code_analysis.sh ~/projects/my-python-project ./analysis

# Review the generated files
ls -l ./analysis/

Technical Details

• Maximum file size: 25MB (configurable)
• Default token limit: 32,000 tokens
• Supported file types: Currently optimized for Python files
• Output format: Markdown with GitHub-flavored syntax highlighting

Contributing

1. Fork the repository
2. Create your 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

License

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

Acknowledgments

• Inspired by the need for efficient code review using AI tools
• Designed to work with various AI platforms including ChatGPT and Perplexity AI
• Built to handle large codebases while maintaining context and readability