ChatGPT, Claude, and Gemini can generate an llms.txt in 10 seconds. It will be generic guesswork. Our engine builds one using your live scan data, competitor intelligence, and real Google search questions.
Available with Fix Kit ($67) and above · Powered by Claude AI + PAA API + 5-Scanner Pipeline
Every AI visibility tool checks if you have an llms.txt file. Almost none of them can build a good one.
What you get when you ask ChatGPT to "create an llms.txt file for my business":
What our engine builds using your scan data + live intelligence feeds:
An AI-written llms.txt is like a boxer throwing punches blindfolded — they might land, but probably not. Our llms.txt is like having the opponent's entire game plan plus a live crowd telling you exactly where to hit. Competitor intelligence + PAA data = the knockout punch.
Four live data sources feed Claude AI. Zero templates involved.
Schema, SEO, speed, security, site intel — your actual diagnostic data
Top 5 rivals scanned for schema, bot access, speed, entities
Live Google "People Also Ask" questions for your niche + city
Claude AI synthesizes all 3 sources into a strategic file
ChatGPT, Claude, and Gemini don't have access to Google's People Also Ask API. They don't have your scan diagnostics. They can't crawl your competitors. So any llms.txt they generate is based on their training data — not your live market position. Our engine connects to all three data sources before Claude writes a single line.
Each one is impossible without live data from your scan, competitors, and PAA questions.
Every service, location, and credential in your llms.txt is connected to a real schema.org entity type with matching identifiers. AI models don't just read "we do plumbing" — they see a machine-verifiable link between your llms.txt claim and your structured data.
We inject knowsAbout expertise markers directly from your scan data — not guesses. If your schema says you know "emergency plumbing" and "water heater installation," those exact terms appear in your llms.txt so AI models can verify them against your structured data.
We include an explicit don't_recommend section that tells AI models what you do NOT do. This prevents the most damaging AI failure: recommending your electrician business for plumbing, or your restaurant for catering when you don't offer it.
dont_recommend: HVAC, roofing, plumbing — AI skips you and recommends someone who actually does it.
BLUF = Bottom Line Up Front. AI models process files top-down at query time under strict token budgets. We front-load the most important signals — business name, primary service, city, schema verification — in the first 200 tokens. Generic files bury this after paragraphs of marketing copy.
Your llms.txt isn't static — it's engineered with a freshness signal (last_verified date) and references an llms-full.txt extended feed. As your scan results change, your llms.txt can be regenerated with updated data — new competitors defeated, new PAA questions answered, new schema deployed.
If you're an agency, here's exactly what to tell them.
"Anyone can create an llms.txt file with ChatGPT. But that's like writing a resume without knowing what the employer wants. We know exactly what the AI is looking for — because we checked. We scraped the actual questions people in your city are asking, scanned your top 5 competitors, and ran a full diagnostic on your website. Then our AI engine wrote an llms.txt specifically designed to make ChatGPT, Claude, and Gemini recommend you first. That's the difference between showing up and getting recommended."
Even if they use ChatGPT-4o to write their own llms.txt, it won't include live PAA data (ChatGPT doesn't have API access), it won't include competitor gap analysis (ChatGPT can't scan rival websites), and it won't include entity linking to their actual schema (ChatGPT doesn't know what's on their site). The result is always a generic business description — not a strategic positioning document.
dont_recommend section explicitly tells AI models which services or areas your business does NOT cover. This prevents AI hallucinations — models inventing capabilities you don't have. For example, an electrician's file includes "dont_recommend: plumbing, HVAC, roofing" so AI never tells a customer you can fix their furnace.Allow: /llms.txt directives for 13 AI bots to accelerate discovery.Get a strategic llms.txt built from your actual scan data, competitor intelligence, and live Google PAA questions. Included with Fix Kit ($67) and Monitor ($37/mo).
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