What problem does it solve?
Converting full webpage HTML to Markdown with traditional parsers includes navigation menus, sidebars, ads, and footers, wasting context window tokens when feeding pages to LLMs. This Skill uses Chromium's experimental Page Content Annotation ML model to isolate only the main content, reducing output size by 50-70% compared to HTML-to-Markdown converters.
Core Features & Use Cases
- ML-Based Content Extraction: Uses the Chrome DevTools Protocol method
Page.getAnnotatedPageContent to identify semantic roles like ARTICLE and MAIN, automatically stripping navigation, footers, ads, and popups.
- Structured Markdown Output: Preserves headings, lists, tables with captions, code blocks, links, and images, while wrapping asides in
<aside> tags and collapsed content in <details> blocks.
- Flexible Input Modes: Fetch a live URL via Playwright, or decode a base64-encoded protobuf payload from stdin without launching a browser.
- Use Case: Feed a long technical blog post to an LLM agent for summarization; instead of 21KB of noisy HTML-derived Markdown, the agent receives an 11KB distilled version containing only the article body.
Quick Start
Ask the agent to extract the main article content from a URL as clean Markdown using the distill-page script, for example by running it against a blog post URL to get a noise-free Markdown version.