llm-boost

What problem does it solve?

This Skill streamlines the process of making content more effective for Large Language Models (LLMs), improving their understanding, efficiency, and output quality.

Core Features & Use Cases

• Documentation Optimization: Enhances documentation (like READMEs) for better AI comprehension and scoring (c7score).
• Skill Optimization: Reduces the token size of Claude Code skills by moving content to reference files, adhering to the 500-line rule.
• Prompt Structuring: Designs effective XML tag structures for clearer LLM instructions and output parsing.
• LLM Parameter Tuning: Provides guidance on setting parameters like temperature and max_tokens for different LLM tasks.
• Use Case: You have a complex Claude Code skill that's too large for efficient loading. Use this Skill to refactor its SKILL.md into a more manageable size by moving extensive examples and API docs to separate reference files.

Quick Start

Use the llm-boost skill to optimize the documentation for the attached file 'README.md'.