What exactly is AiVIS Cite Ledger?

AiVIS Cite Ledger is an evidence-backed AI citation audit and remediation system. It measures how AI models, ChatGPT, Perplexity, Claude, and Google AI, interpret, trust, and cite your web content. The result is a 0–100 CITE LEDGER score across seven weighted dimensions, with BRAG evidence-linked findings and prioritized fixes.

How is this different from Semrush, Ahrefs, or Clearscope?

Traditional SEO tools optimize for keyword ranking in traditional search results. AiVIS Cite Ledger audits citation readiness, the specific signals that determine whether AI answer engines retrieve and cite your content. A page can rank #1 on Google and be completely invisible to AI answer synthesis.

What is BRAG and how does it make findings trustworthy?

BRAG stands for Based-Retrieval-Auditable-Grading. It ties every audit finding to a real, traceable element on your page, a specific heading, schema block, meta tag, or content section, each carrying a unique evidence ID. You can open the element, verify the finding, and recheck it after a fix. No black boxes.

Is the free tier genuinely useful, or just a teaser?

The Observer (free) plan gives you a full composite CITE LEDGER score and all seven dimension letter grades, so you can see exactly where you stand and which categories are hurting you. BRAG evidence IDs and prioritized fix packs require a paid plan. Three audits per month, no credit card.

What Is llms.txt, and Does Your Site Actually Need One? | AiVIS Cite Ledger Blogs

By R. Mason · 2026-06-02 · 7 min read · AEO

llms.txt is real, easy to add, and widely overhyped. Here is the honest version: what it is, who honors it, and where it sits in your priority list.

Key Takeaways

llms.txt is a community proposal (llmstxt.org, 2024), not a W3C/IETF standard.
Google AI Overviews does not use llms.txt; ChatGPT and Claude do not depend on it to cite you.
A missing llms.txt does not block citations, it is a low-severity, positive signal only.
AiVIS scores it under AI Readability, generates a correct file, and validates yours, without inflating its weight.
Higher-impact priorities first: robots.txt access, Organization/SoftwareApplication schema, FAQPage, direct-answer blocks.

Article

llms.txt is a plain-text file you place at your domain root, yourdomain.com/llms.txt, that gives AI crawlers a curated map of your most important pages. It was proposed by Jeremy Howard (answer.ai) in 2024, and the spec lives at llmstxt.org.

It is having a moment. It is also widely oversold. Here is the honest version, the same one our own audit engine uses.

What it actually is

A community proposal, not an IETF or W3C standard. A typical file looks like this:

# Your Company

A one-paragraph description of what you do.

Docs

[Getting Started]: https://example.com/docs/start
[API Reference]: https://example.com/docs/api

Product

[Pricing]: https://example.com/pricing

About

[About]: https://example.com/about

The idea is to hand AI crawlers a clean, link-first summary so they spend their attention on your canonical pages instead of guessing.

Who actually reads it, and who does not

This is where most posts get it wrong, so we will be blunt:

Google AI Overviews does NOT use llms.txt. Google relies on its standard index for AI answers.
ChatGPT and Claude do not depend on it to crawl or cite you. Their crawlers use normal web access.
Partial, evolving adoption exists among some Perplexity and Anthropic-adjacent crawlers.

In other words: a missing llms.txt does not block your citations on Google, ChatGPT, or Claude. Anyone telling you llms.txt is the key to AI visibility is selling you something.

So why bother at all?

Because it is cheap, harmless, and forward-leaning. It costs ten minutes, cannot hurt you, and positions you well if adoption grows. In the AiVIS Cite Ledger scoring model it is exactly what the evidence supports: a low-severity, positive AI-readability signal, not a hard blocker. We surface it under the AI Readability dimension, we generate a correct llms.txt for you in the fix output, and we validate the one you have. We do not inflate its weight, because our own citation tests do

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