How to turn any webpage into structured data for your LLM

Your LLM can reason, write code, and hold long conversations. Ask it to read a webpage and it falls apart. Either it can't access the URL at all, or you feed it raw HTML and burn 50,000 tokens on navigation bars, cookie banners, and CSS class names. I've been building webclaw to fix this. It's a web extraction engine written in Rust that turns any URL into clean, structured content. No headless browser. No Selenium. Just HTTP with browser-grade TLS fingerprinting. My first post covered how the TLS bypass works. This one covers what happens after you get the HTML: turning it into something an LLM can actually use. The token waste problem A typical webpage is 50,000 to 200,000 tokens of raw HTML. The actual content, the article text, the product info, the documentation, is usually 500 to 2,000 tokens. The rest is structure, styling, and UI elements that your LLM processes, reasons over, and bills you for. If you're building a RAG pipeline, those noisy tokens pollute your vector space. Yo