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News/ Docs/ The docs, rebuilt: a linear journey with Ctrl+K search
The docs, rebuilt: a linear journey with Ctrl+K search
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The docs, rebuilt: a linear journey with Ctrl+K search

TL;DRThe documentation is now a structured, top-to-bottom journey — six categories from your first pipeline to publishing packages — with a Ctrl+K search palette, a sticky nav and table of contents, and a plain-markdown view of every page that coding agents and LLMs can read directly.

Docs you can actually follow#

Reference pages are easy; a path is hard. We rebuilt the docs as a single linear journey, organized into six categories — from Start (install and run your first pipeline) through Building Tools, Examples, the UI Toolkit, Packages, and the full API Reference. Each category owns a section of the left nav, so you always know where you are and what comes next.

Ctrl+K to find anything#

Every docs page ships a search palette: hit Ctrl+K (or Cmd+K), type, and jump. Results rank by title and headings, with full keyboard navigation. No more hunting through the sidebar.

Built for humans and agents#

Long pages get a sticky table of contents that tracks where you are as you scroll. And because coding assistants increasingly read our docs too, every page has a plain-markdown twin — append .md to any docs URL for a clean, token-efficient view, served noindex with a canonical link back to the HTML. The whole site is indexed for AI at /llms.txt.

Dive in#

Open the docs, press Ctrl+K, and build something. We're filling in more guides and examples continuously.

Frequently asked questions

How do I search the docs?

Press Ctrl+K (or Cmd+K) anywhere in the docs to open the search palette, then type — results rank by title and headings, and Enter jumps you straight there.

What is the .md view?

Append .md to any docs URL to get the raw markdown of that page — a token-efficient, noindex view that coding assistants and LLMs read directly, with a canonical link back to the HTML.

Is there a machine-readable index?

Yes — /llms.txt lists the site's pages for AI answer engines, and /llms-full.txt inlines the full text, so tools can consume the docs without scraping HTML.

References

  1. Read the docs
  2. llms.txt

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