One truth. Every place AI reads it.

Stop Maintaining Your
llms.txt by Hand.

State a fact about your business once, verified, in CiteMetrix. It becomes your llms.txt file, your schema.org markup, and the ground truth your hallucination detection checks AI against — and CiteMetrix tells you when any of it falls out of date.

1 clickGenerate llms.txt from your verified facts
2Expressions from one fact: llms.txt + schema.org
🔄Drift detection, internal and live
✅Verified-only publish gate

The Problem With Hand-Written Files

llms.txt goes stale the moment you stop watching it

You write an llms.txt file once, upload it, and move on. Then your pricing changes, or a product ships, or a certification lapses — and the file sitting on your server telling AI crawlers about your business is now quietly wrong. Nothing tells you. Nothing checks. The same problem hits your schema.org markup, usually maintained by hand in a completely different place, saying something slightly different.

Two files, two sources of truth, two ways to drift out of sync with reality — and no way to know until a customer tells you AI got something wrong.

One Repository, Every Expression

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1. State the Fact Once

Add a Brand Fact — category, key, value — and mark it verified once you’ve confirmed it’s accurate. Only an Owner or Admin can verify a fact; nothing reaches AI crawlers on a guess.

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2. Opt It Into Publishing

Flip a fact’s publish toggle and it’s eligible for your public llms.txt. Not every verified fact belongs in a crawler file — internal notes and competitor data stay private by default.

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3. Generate Both Expressions

One click builds your llms.txt from verified + published facts. The same facts deterministically build your Organization schema.org markup — no AI, no placeholder text, just your real facts mapped to real schema fields.

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4. CiteMetrix Watches for Drift

Change a published fact and your llms.txt shows an amber warning until you regenerate. Click “Check my published file” and CiteMetrix fetches your live file to catch the file you generated but forgot to upload.

Not Just an llms.txt Generator

The part no other tool does

Any tool can hand you a text file. CiteMetrix closes the loop: your monitoring surfaces that AI is saying something wrong about your brand → you fix it at the source, in your Brand Facts repository — not in three different files — and regenerate → Correction Proof then reports whether the AI platform actually updated its answer afterward.

Most tools that help you maintain a crawler-facing file can show you the problem. None of them can show you whether fixing it worked. CiteMetrix can, because the same fact that publishes to llms.txt is the fact your hallucination detection checks AI against.

Built to Be Trusted

Why the verified-only gate matters

  • Only an Owner or Admin can mark a fact verified — unconfirmed facts never reach a public file, even if they’re already in the system
  • Publishing an unverified fact to an AI crawler as authoritative is exactly the kind of mistake CiteMetrix exists to catch — the gate applies to CiteMetrix’s own output too
  • Schema.org markup is built deterministically from your facts — not AI-generated, no placeholder text slipping into a live page
  • Bulk-import a spreadsheet of facts and the same gate applies: verified/publish status from a CSV is only honored when the account owner explicitly confirms it reviewed the data

Common Questions

What’s the difference between this and just writing an llms.txt file myself?
A hand-written file is correct on the day you write it and silently wrong after that. CiteMetrix generates the file from a repository you’re already maintaining for accuracy monitoring, so it can tell you exactly when the live file has fallen behind — both when a fact changes and when the file itself was never re-uploaded.
Does this replace my existing schema.org markup?
It’s an additional, deterministic Organization schema build sourced from your verified facts — distinct from CiteMetrix’s AI-based Schema Generator and Schema Advisor tools, which analyze and suggest markup for any page. Use whichever fits: the facts-based build for your core organization identity, the AI tools for page-level structured data.
What happens if I publish a fact that turns out to be wrong?
Un-publishing is always allowed, by anyone with fact-management access. Un-verifying and re-verifying is how you correct it at the source; regenerate afterward and the fix propagates to llms.txt and schema.org together.
Can I bulk-import facts instead of adding them one at a time?
Yes — CSV import supports category, key, value, and criticality for every plan. Verified status and publish status can also be set from the CSV, but only take effect when the account owner checks a confirmation box acknowledging they’ve reviewed the data — the same trust bar as verifying a fact by hand.

One Fact.
Every Place AI Looks.

Included on every plan — llms.txt generation, schema.org from your facts, and drift detection.

See Plans and Pricing