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Use case·SaaS and documentation//LLMReady

Docs that coding agents and assistants can read in one request.

Developers ask an assistant how to call your API. If the docs hide behind a single-page app, the assistant guesses, and guesses wrong.

docs.acme-api.example/referenceClaude-User
HTTP 200<div id="root"></div>Please enable JavaScriptNo llms.txt
AI readiness
29
docs.acme-api.example/reference.mdserved

API reference

Authenticate every request with a bearer token.

Endpoints

  • POST /v1/scan starts a scan
  • GET /v1/scan/{id} returns the result
  • GET /v1/bots lists known bots
llms.txtmarkdownjson-ld
AI readiness
94
What LLMReady does

What changes for this job.

  • Publishes llms.txt and a markdown twin of every docs page, refreshed on every deploy
  • Reports which agents fetch which docs pages and which get errors
  • Verifies that coding-agent traffic is real before serving it
Checks that matter most

Start with these three.

/llms.txt

llms.txt file

A short guide to your best pages, written for language models. LLMReady checks that it exists, loads and links to live pages.

h1 to h3

Headings and structure

Clear headings, one topic per page and answers placed near the question, so a model can lift them cleanly.

.md

Markdown versions

A plain markdown copy of each key page is the easiest thing for a model to read. LLMReady tests whether yours exist.

FAQ

Questions on this use case.

01Does it replace my docs tool?
No. It sits in front of whatever serves your docs and adds the machine-readable layer.
02Which standards does it follow?
The llms.txt proposal and plain markdown. The proposal is not read by every AI system yet, so LLMReady reports which parts are widely supported.
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