// free tool · runs in your browser · validated live
llms.txt Generator
Fill the fields, get a file that actually follows the llmstxt.org spec — H1, summary blockquote, sectioned link lists — with a validator re-checking the output on every keystroke. This site ships its own llms.txt built the same way; you can read it live for a real-world example.
Quick answer
An llms.txt file is a markdown site map for AI systems, served at yourdomain.com/llms.txt. The format, proposed by Answer.AI in September 2024, needs one H1 with your site name, a blockquote summary, and H2 sections of annotated links. This generator produces and validates that structure in your browser.
Generator
Your llms.txt
# Untitled site
✓ Spec-valid · 0 section(s), 0 link(s) — save as /llms.txt at your site root
// the honest pitch
What llms.txt does and does not do in 2026
The skeptic case first: Google has said plainly that Search does not use llms.txt, and no AI platform has committed to it as a ranking input. If a tool page promises llms.txt will boost your AI visibility score, close the tab. The realist case: AI coding assistants fetch it for documentation sites, some answer engines read it when summarizing a domain, and it is the one place you control the exact wording an AI sees first. Ten minutes of work for a maybe is a good trade; ten hours would not be.
What separates a useful llms.txt from a token one is curation. Do not mirror your sitemap — pick the 10-30 pages that answer "what is this site and can I trust it", and write the notes like you are briefing a fast-reading intern. Our own file leads with what we sell, real prices, and the refund terms, because those are the facts we want quoted correctly. Check any site's AI crawler access — including whether bots can even reach your llms.txt — with the AI crawler checker, and see the full picture in the AI Search Visibility Toolkit.
// common questions
llms.txt — common questions
- What is an llms.txt file?
- llms.txt is a markdown file at your site root that gives AI systems a curated map of your most important content — a site name, a one-sentence summary, and sections of annotated links. Jeremy Howard of Answer.AI proposed the format in September 2024 to solve a real constraint: AI context windows cannot hold your whole site, so you choose what they read first.
- Does llms.txt improve AI search rankings?
- The honest 2026 answer: evidence for a direct ranking effect is thin, and Google has said it does not use the file. Its proven value is narrower — AI coding assistants and agents that fetch documentation use it, and assistants that do read it represent your site more accurately. It costs ten minutes and a text file; price the bet accordingly.
- Where do I put the file once generated?
- Save it as llms.txt at your web root, so it resolves at yourdomain.com/llms.txt — the same location convention as robots.txt. Static hosts: drop it in the public folder. Verify by opening the URL in a browser; if you can read it, so can an AI.
- What is the difference between llms.txt and llms-full.txt?
- llms.txt is the curated index: links plus short notes. llms-full.txt is an optional companion holding the complete flattened content of your docs in one file, for tools that want everything in a single fetch. Most non-documentation sites only need llms.txt.
- What should a digital product shop put in its llms.txt?
- The sections AI assistants actually quote: what the shop sells with prices, the refund policy summary, and direct product links with one-line descriptions. Ours lists all 19 products with prices and a quick-answers section — it doubles as the brief we want ChatGPT to read before describing us.
- Does this generator upload my data anywhere?
- No. Generation and validation run entirely in your browser — nothing you type leaves your device. The validation badge re-checks the output against the structural rules of the spec on every keystroke.
// llms.txt is step one of eleven
AI search visibility is a system, not a file.
The AI Search Visibility Toolkit covers the other ten steps: citability scoring, crawler audits, schema, and platform-specific optimization.
See the toolkit →