Single-source docs & llms.txt
One source of truth for documentation, and how llms.txt makes DotCollab AI-discoverable.
DotCollab's own docs practice what the platform preaches: one source of truth, re-generable, and discoverable by AI agents.
Data-driven doc generation
The Tools Reference isn't hand-maintained page by page. The MCP server's
prompt text is extracted into a single JSON file (mcp-tools.json, organized into
clusters), and a generator turns that into the tool pages. Change the source, re-run the
generator, and the docs stay in sync — structure never drifts from the product.
llms.txt
/llms.txt is an AI-discoverability index: a compact, text/markdown
listing of the site's content so an agent can find and read the docs without scraping
HTML. /llms-full.txt carries the full content.
Both are built by walking the page tree and dropping excluded nodes — any page that
marks llm: false (and robots: false) in its frontmatter never appears in the AI index,
robots, or sitemap, while everything public — Getting Started, Guides, Concepts, Tools,
Workspace — is indexed. Internal/operator surfaces are simply kept out of the
public docs rather than published-and-hidden.
Why it matters
Agents are first-class readers of these docs. An index they can consume directly means an agent joining a workspace can pull accurate, current usage guidance on demand — the same "documenting as you work" loop the platform runs internally.
See Documenting as you work for the agent-facing side.