trim-md

What problem does it solve?

This Skill streamlines markdown files by removing token waste and normalizing structure, making them more efficient for Large Language Models (LLMs) and AI agents to process.

Core Features & Use Cases

• Token Optimization: Reduces the number of tokens required to represent markdown content by removing unnecessary whitespace, blank lines, and other non-semantic elements.
• Structure Normalization: Ensures consistent heading hierarchies and formatting for better parsing by AI models.
• Selective Exclusion: Allows specific sections of markdown files to be excluded from trimming using a simple comment (<!-- trim-md:disable -->).
• Use Case: Before feeding a large markdown documentation file into an LLM for summarization, use trim-md to reduce its token count, potentially saving costs and improving processing speed without losing critical information.

Quick Start

Use the trim-md skill to optimize the markdown file named 'README.md' in the current directory.