Markdown Optimized Content Normalization

via “markdown-optimized content normalization”

** - Web content fetching and conversion for efficient LLM usage

Unique: Applies LLM-specific optimization rules during markdown conversion (e.g., collapsing excessive whitespace, normalizing heading levels, removing redundant formatting) rather than generic HTML-to-markdown conversion, reducing token consumption by 15-30% compared to naive conversions

vs others: Purpose-built for LLM consumption unlike general HTML-to-markdown converters; balances readability with token efficiency through heuristics tuned for language model processing patterns