llm-tldr

What problem does it solve?

This Skill tackles the challenge of AI agents struggling with large codebases by providing highly compressed and rapidly searchable code intelligence, drastically reducing token usage and query times.

Core Features & Use Cases

• Token Optimization: Achieves up to 95% token savings by analyzing code into structured formats.
• Speed Enhancement: Delivers 300x faster queries compared to raw code analysis.
• Codebase Understanding: Enables AI agents to perform tasks like debugging, refactoring, and semantic search across multiple languages.
• Use Case: An AI agent needs to debug a complex issue in a large Python project. Instead of processing thousands of lines, it uses llm-tldr to get a concise, relevant code context, significantly speeding up the debugging process.

Quick Start

Use llm-tldr to get a summary of the main function in the current project.