Build a valid llms.txt file in your browser, then save it at your site root so AI engines have a clean summary of who you are and which pages matter.
Quick Answer: This free tool builds an llms.txt file in the emerging Markdown format proposed by Jeremy Howard of Answer.AI: an H1 site name, a one-line summary blockquote, your site link, an optional note, and a curated list of your key pages. Fill the fields, press Generate, copy the result, and save it as llms.txt at your domain root. Everything runs client-side; nothing you type leaves your browser.
Build your llms.txt
How to use it
- Enter your site name and one-line summary. The name becomes the H1; the summary becomes the blockquote an AI engine reads first. Keep the summary to a single accurate sentence: who you are, where you operate, what you sell.
- Add your site URL. If you leave off the scheme, the tool adds
https://for you so the links stay valid. - Write the optional note. This is the "what you want AI to understand about you" paragraph: certifications, service area, what makes your offer specific. Skip it if the summary already covers it.
- List your key pages. Add a row for each page that matters most: Services, About, Contact, and your strongest articles. Give each a clear label, the full URL, and an optional one-line description.
- Generate, copy, and publish. Press Generate, review the file in the result box, copy it, and save it as
llms.txtat your domain root.
Why it matters
An llms.txt file maps to Vector 2, Anchor, in Formative Digital's 12 Vectors methodology. Anchor is the work of making an AI engine resolve your business as a clear, single entity: consistent name, defined summary, a known set of canonical pages. When an engine retrieves and synthesizes an answer, it leans on entities it can resolve cleanly. A tidy llms.txt is one more place where your name, your summary, and your priority URLs agree with each other.
Here is the honest part. As of 2026, no major AI engine has publicly confirmed it reads llms.txt at retrieval time, and the file is a community proposal rather than a ratified standard. So this is not a citation lever on its own. It is cheap, accurate scaffolding: minutes to publish, no downside, and a head start if adoption grows. The signals that actually move your citation rate are entity validation, a complete schema graph, passage-level content structure, and citations on the corpus the engines trained on. The file is a clean front door. The building behind it is the work.
The tool gives you the front door. We build what is behind it.
An llms.txt file is a five-minute job. Becoming the business an AI engine actually recommends is the Anchor, Embed, Structure, and Cluster work that sits behind it. Our Content Engine service produces the schema, passage-structured content, and entity signals at the volume that moves a citation rate, run by the Formative Forces orchestrated agent system and backed by a 12-month Results Guarantee.
The tool shows you the gap. We close it. Book a free AI visibility audit and we will read your current footprint across ChatGPT, Perplexity, and Google AI Overviews, then tell you which Vectors are working and which are not.
Frequently Asked Questions
What is an llms.txt file?
An llms.txt file is a plain-text Markdown file you place at the root of your domain (for example, yoursite.com/llms.txt) to give AI engines a clean, structured summary of who you are and which pages matter most. The format was proposed by Jeremy Howard of Answer.AI in 2024. It starts with an H1 site name, a blockquote one-line summary, an optional note, and a list of key pages as Markdown links. It is a curated map of your site for machines, not a crawl directive like robots.txt.
Is llms.txt an official standard that AI engines obey?
Not yet. llms.txt is an emerging community proposal, not a ratified standard, and as of 2026 no major AI engine has publicly confirmed it reads the file at retrieval time. We are honest about that. The value today is low-cost and low-risk: a clean, accurate llms.txt costs minutes to publish, gives a machine-readable summary of your entity and priority pages, and positions you if adoption grows. Treat it as one supporting signal, not a visibility guarantee.
Where do I put the llms.txt file once I generate it?
Save the generated text as a file named exactly llms.txt and upload it to the root of your domain so it resolves at https://yoursite.com/llms.txt. The same level robots.txt and sitemap.xml live at. On a static host you drop it in the public root folder. On WordPress or Shopify you may need a file-upload app or a redirect rule, since those platforms do not expose the root directory directly. Confirm it loads in a browser at the /llms.txt path.
Does this tool send my site data anywhere?
The generator runs entirely in your browser with vanilla JavaScript. The llms.txt body is assembled on your own device from the fields you fill in, the Copy and Download buttons use your browser, and the preview is built locally. The only point at which anything is sent is if you choose to submit the short capture form to reveal the full file, which notifies Formative Digital so we can help you publish it. The file generation itself never leaves your browser.
How does llms.txt fit into generative engine optimization?
It is a small piece of the Anchor Vector: helping an AI engine resolve your business as a clear entity with a defined summary and a set of canonical pages. On its own, an llms.txt file does not move your citation rate. The signals that move it are entity validation, schema graph completeness, passage-level content structure, and citations on the corpus the engines were trained on. The file is a tidy front door; the building behind it is what gets you cited.