LLM Docs Optimizer

This skill optimizes project documentation and README files for AI coding assistants and LLMs like Claude, GitHub Copilot, and others. It improves documentation quality through multiple approaches: c7score optimization (Context7's quality benchmark), llms.txt file generation for LLM navigation, question-driven content restructuring, and automated quality scoring across 5 key metrics.

Version: 1.3.0

Understanding C7Score

C7score evaluates documentation using 5 metrics across two categories:

LLM Analysis (85% of score):

1. Question-Snippet Comparison (80%): How well snippets answer common developer questions
2. LLM Evaluation (5%): Relevancy, clarity, correctness, and uniqueness

Text Analysis (15% of score): 3. Formatting (5%): Proper structure and language tags 4. Project Metadata (5%): Absence of irrelevant content 5. Initialization (5%): Not just imports/installations