Reachability check
Whether the file exists at /llms.txt, returns a 200, and is served as plain text rather than as an HTML error page dressed up as a file.
Free AEO Tool
Paste or fetch your llms.txt and see whether it parses, what a crawler actually reads from it, and what is missing. It checks that the file is reachable, that its structure parses, that every link it lists resolves, and that it does not contradict your robots.txt. Free, no signup, no card.
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Fetching /llms.txt...
That the file is reachable at the expected path, that its structure parses, that the links it lists resolve, and that it is not contradicting your robots.txt. A file that 404s or lists dead URLs is worse than no file, because it spends a crawler's attention and returns nothing.
Pair it with the free llms.txt generator: generate the file, publish it, then validate that a crawler can actually use it.
Whether the file exists at /llms.txt, returns a 200, and is served as plain text rather than as an HTML error page dressed up as a file.
Whether the Markdown parses, whether the title and summary a crawler looks for are present, and how many sections and links it finds.
Every URL the file lists, resolved. Dead links, redirect chains and bare domains are reported individually rather than as a count.
Whether your llms.txt points crawlers at paths your robots.txt tells them not to fetch. This is the most common real fault and the easiest to miss.
We look for the file at the root of your domain, which is where crawlers look.
Structure, headings, summary and every link it lists, read the way a crawler would read them rather than the way they look in an editor.
What works, what is broken, and what to change. No score to interpret on its own.
This free tool is useful for:
After running the check, you may receive a result like this:
llms.txt Validation Website: https://example.com File URL: https://example.com/llms.txt Overall: 68/100 File status: - Reachable at /llms.txt: Yes - Content type: text/plain - Parses as Markdown: Yes - Size: 4.1 KB Structure: - H1 title present: Yes - Summary blockquote present: Yes - Section headings found: 6 - Links found: 34 Link health: - Resolving: 31 - Redirecting: 2 - Dead (404): 1 What needs attention: - One listed URL returns 404: https://example.com/old-pricing - Two URLs redirect, so a crawler spends two hops to reach the real page. - Your robots.txt disallows /resources/, but llms.txt lists four URLs under it. A crawler that respects robots.txt cannot fetch what this file points it at. - Three links use a bare domain rather than an absolute URL. Recommended fixes: 1. Remove or update the dead URL. A file listing dead links is worse than no file. 2. Point the two redirecting entries at their final destinations. 3. Resolve the robots.txt conflict, either by allowing /resources/ or by removing those entries from llms.txt. 4. Use absolute URLs throughout so there is nothing to resolve against. 5. Re-run this check after publishing the corrected file.
The report is written to be read rather than scored. The goal is not to grade the file. It is to tell you whether a crawler can use it, and exactly which line to change if it cannot.
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GEO guide
llms.txt is a plain text file at the root of your domain that points a crawler at your clean, machine readable content. It is a Markdown document with a title, a short summary, and sections of links with descriptions.
Treat it as a signal rather than a guarantee. No file will make a model recommend you on its own, and anyone promising that is overselling it. What the file does is remove one excuse for being misread: if a model cannot find a clear statement of what you do, it will infer one.
Publishing it is cheap, which is the honest argument for having one. Getting it wrong is cheap too, which is the argument for checking it.
# Your Brand > Short AI-readable summary ## Services * [Pricing](/pricing) * [About](/about)
llms.txt is a plain text file at the root of your domain that points a crawler at your clean, machine readable content. It is a Markdown document with a title, a short summary, and sections of links with descriptions.
Treat it as a signal rather than a guarantee. No file will make a model recommend you on its own, and anyone promising that is overselling it. What the file does is remove one excuse for being misread: if a model cannot find a clear statement of what you do, it will infer one.
Publishing it is cheap, which is the honest argument for having one. Getting it wrong is cheap too, which is the argument for checking it.
The two files do opposite jobs. robots.txt tells a crawler where it may not go. llms.txt tells a crawler where the good content is. When they contradict each other, the crawler obeys robots.txt and your llms.txt entry is wasted.
This happens most often after a redesign, when a path is blocked for a good reason and the llms.txt file is not updated to match. Nothing warns you, because neither file knows the other exists.
A path listed in llms.txt that robots.txt disallows
A sitemap reference in one file and not the other
Staging or test paths left in either file after launch
AI crawlers blocked in robots.txt while llms.txt is published for them
An H1 with your brand name
A one-paragraph summary a model can lift and attribute
Sections grouping your pages by what they are for
Absolute URLs, so there is nothing to resolve against
A short description per link, saying what the page answers
Nothing listed that robots.txt blocks
Use the Free llms.txt Validator when:
A validated llms.txt is a floor, not a result. It makes you readable. Being recommended is a separate job, and it is the one Sophyx does.
Validation tells you a crawler can read your site. It does not tell you what an assistant says about you when a buyer asks. That is a different check, and it is free too: thirty prompts, re-checked every two weeks, no card. See which answers name a competitor instead of you, then have us write the correction and publish it on your own domain.
See what AI says about youCombine this tool with the other free Sophyx toolkits to improve crawlability, structured data, LinkedIn clarity, and AI mention visibility.
Continue learning with guides, platform features, and AI visibility resources across the site.
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