llm-context.py

📋 Overview:

This report summarizes the content of a GitHub repository webpage for "llm-context.py," a tool designed to facilitate code and text sharing with Large Language Models (LLMs). The tool supports both Model Context Protocol (MCP) for direct LLM integration and clipboard workflows for broader compatibility. Key features include profile-based customization, smart file selection based on .gitignore patterns, and experimental code outlining support.

⭐ Key Points:

• LLM Context is a tool for injecting code and text into LLM chat interfaces.


• Supports Model Context Protocol (MCP) and clipboard workflows.


• Profile-based customization enables task-specific configurations.


• Utilizes .gitignore patterns for intelligent file selection.


• Includes experimental code outlining support.


• Configuration files were converted from TOML to YAML in v 0.2.9.


🔍 Main Findings:

• LLM Context is optimized for projects that fit within an LLM's context window.


• Direct integration is available with Claude Desktop via MCP.


• CLI commands support initialization, profile switching, file selection, context generation, prompt generation, and file processing.


• The tool evolves from previous AI-assisted development tools, acknowledging inspirations and collaborations.


• Users are warned about potential configuration file overwrites during updates and advised to use version control.


📊 Details:

• Installation is recommended via the uv package manager.


• Code outlining support requires installing with the "[outline]" extra.


• The project is licensed under Apache License 2.0.


• The project has 125 stars and 10 forks.


• Languages used: Python (85.0%), Scheme (8.7%), and Jinja (6.3%).

🎯 Conclusion:
LLM Context is presented as a versatile tool to enhance AI-assisted software development by streamlining the process of sharing relevant project information with LLMs. The tool aims to improve LLM performance in tasks like code review and documentation by providing context-aware information.