SEO

Audit or draft an llms.txt

Check whether the site has an llms.txt, whether it follows the spec and points at the pages that matter, and if it is missing draft one from the pages Search Console shows people actually find, so AI assistants get a curated map of the site instead of guessing.

  • Do we need an llms.txt?
  • Draft an llms.txt from our top pages
  • Is our llms.txt pointing at the right pages?

The playbook

An llms.txt is a short markdown file at the site root that tells AI assistants what the site is and which pages to read first. It is the AI-era equivalent of a curated sitemap. Adoption by crawlers is uneven, so it is a cheap bet rather than a guarantee, but a good one takes an hour and a bad one misleads every assistant that does read it.

Sequel supplies the traffic data that decides what belongs in the file. Fetching the existing file and the pages uses your own browsing.

Steps

  1. Fetch what exists. Request /llms.txt and /llms-full.txt. A 404 on the first means you are drafting; skip to step 4. If it exists, keep going.

  2. Validate the structure. The spec expects: one H1 with the site or project name, a blockquote with a one-paragraph summary, optional prose, then H2 sections each containing a list of - [Title](url): description entries, with an optional final section named Optional for lower-priority links. Report deviations.

  3. Validate the links and the coverage. Fetch every listed URL and check it returns 200, is not noindex, and is the canonical form. Then pull google_search_console.query with dimensions: ["page"], 90 days ending 3 days ago, rowLimit: 300, and list the top 50 pages by clicks that the file does not mention. Those are the omissions that matter.

  4. Draft, if missing. From the same Search Console call, take the top pages by clicks and group them into sections that match how the site is organised (documentation, guides, product, pricing, blog). Fetch each chosen page to write a one-line description from its title and meta description in your own words. Keep the main file under about 100 links; push the rest to Optional or to llms-full.txt. Do not include gated, private, login or utility URLs.

  5. Report. For an audit: the structural findings, the broken or non-canonical links, and the missing top pages. For a draft: the complete file in a markdown code block, ready to save at the site root, plus a note on where it goes and that it does not replace the XML sitemap. Continue with ai-crawler-access-check if the crawlers that would read it are blocked.

Gotchas

  • Do not promise citations. The file helps assistants that read it; not all do. Present it as low-cost hygiene.
  • Curate, do not enumerate. A file listing every URL is a sitemap with extra steps. The value is the selection and the descriptions.
  • Keep it maintained. A stale llms.txt pointing at moved pages is worse than none. Suggest regenerating it when the top pages change.
  • Markdown versions of pages are a separate convention. Some sites also serve .md copies of pages; that is optional and not required for llms.txt to be useful.
  • Search Console lags 2 to 3 days. End the window 3 days back.

Install

Install Sequel skills into your agent

Pick your app and Sequel installs itself: a one-click link where the client supports it, that client’s own few steps where it doesn’t. The playbooks come with the server: your agent sees that this playbook exists and reads it when a question matches.

Claude, ChatGPT, Cursor, VS Code, Claude Code, Codex, Grok, Muse, dots and any other MCP app

Already have an MCP client?

https://api.sequel.sh/mcp

Add it as a remote (streamable HTTP) server and sign in when prompted. Skills come with it; nothing else to install. Manual setup per client

Choose your app

  • Claude

    One click, opens in the app

  • Cursor

    One click, opens in the app

  • VS Code

    One click, opens in the app

  • ChatGPT

    Turn on developer mode, then add Sequel. About two minutes.

  • Claude Code

    Run one command, then sign in with /mcp.

  • Codex

    Run one command, then sign in.

  • Gemini CLI

    Run one command, then sign in with /mcp auth.

  • Grok

    Add Sequel as a connector and sign in.

  • Grok Bot

    Paste this to the bot. It registers Sequel and asks you to sign in.

  • Muse

    Muse writes its own connector. One message is the whole setup.

  • dots

    Add Sequel in ChatGPT; your dot picks it up with no extra step.

  • OpenCode

    Add Sequel as a remote server from the OpenCode CLI.

  • Other MCP app

    Any client that speaks remote MCP can connect with this URL.

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See who links to the site and whether the backlink profile is healthy: referring domains, authority distribution, anchor text mix, dofollow share and concentration risk from Ahrefs, optionally compared against a competitor.

FAQ

Frequently asked questions

What is llms.txt?
A plain-text file served at /llms.txt that tells AI language models which pages on your site are worth reading and how your content is structured. It follows the llmstxt.org convention and is read by AI assistants and crawlers that look for it before deciding what to index from your site.
How is llms.txt different from a sitemap?
A sitemap is for search engine crawlers and lists every URL. llms.txt is for AI models and lists only the most useful pages, with enough context for the model to understand what the site does and which pages answer which questions. It is curated, not exhaustive.
Does having an llms.txt file improve my visibility in ChatGPT or Claude answers?
It increases the chance that AI crawlers prioritize and correctly index your important pages. Whether that leads to more citations depends on whether your content is a good answer to queries the assistant is asked. llms.txt helps the model find the right content; it cannot make weak content rank.
What should my llms.txt file include?
Your site name and one-sentence description, a short list of your most useful pages with a sentence of context each, and optionally a pointer to an llms-full.txt with extended content. Pages that answer specific questions, documentation, and guides are the best candidates.
Can an AI agent audit and draft my llms.txt?
Yes. The agent reads your current llms.txt if one exists, checks whether key pages are included, and drafts an updated version. No Sequel-specific connection is required: the agent uses its own browsing. Sequel includes the llms-txt-audit-and-draft playbook.

Put this playbook to work

Connect a source, ask the question, and the agent follows these steps. Free to start.