FREE DEVELOPER TOOL · AEO & AI SEO
llms.txt & ai.txt Generator
Format spec-compliant markdown site summaries, key discovery endpoints, and AI crawling permissions in seconds. Make your product instantly readable for ChatGPT, Claude, Perplexity, and Cursor.
- Agents:ChatGPT · Claude · Cursor
- Exports:llms.txt · ai.txt · ZIP bundle
- Token Load:~90% less vs HTML
1. Site & Brand Identity
Required2. Core Pages & Key Sections
3. Documentation, Endpoints & Guides
4. AI Permissions & Crawling Rules (ai.txt)
AEO Standard# Loading output...How to Deploy to Your Site (30 Seconds)
- Download or copy the generated
llms.txtandai.txt. - Place both files directly in your website's root
public/directory (alongsiderobots.txt). - Deploy your site. Test in browser at
https://yourdomain.com/llms.txt.
Why Traditional SEO Fails on AI Answer Engines (AEO)
For twenty years, search engine optimization focused on feeding Google's PageRank algorithm: stuffing HTML meta tags, optimizing JSON-LD schema, building backlink profiles, and rendering heavy JavaScript client-side. But modern developers and founders no longer search the web solely via Google blue links—they prompt ChatGPT, Perplexity, Claude, and IDE coding agents like Cursor.
When an LLM visits your website to answer a user's question, it encounters mega-byte HTML bundles, React hydration scripts, pop-up modals, and tracking tags. Parsing this noise burns through precious context window tokens. llms.txt solves this by creating a dedicated, token-efficient markdown layer for machines.
HTML Meta SEO vs. AI Markdown AEO
| Dimension | Traditional SEO (Google) | Answer Engine Optimization (AEO) |
|---|---|---|
| Primary Consumer | Googlebot, Bingbot crawlers | LLMs (ChatGPT, Claude, Perplexity, Cursor) |
| Format of Truth | HTML DOM + OpenGraph Meta Tags | Structured Markdown (/llms.txt, /ai.txt) |
| Context Overhead | Heavy (50KB–500KB HTML noise) | Minimal (1KB–5KB plain markdown) |
| Discovery Method | sitemap.xml | /llms.txt + RFC 9727 API Linksets |
| Goal | Rank on 10 blue links page | Be directly cited in AI-generated answers |
The Anatomy of a Spec-Compliant llms.txt
According to the llmstxt.org specification, a well-formed file contains three essential sections:
- H1 + Blockquote Summary: The name of your site followed immediately by a single markdown blockquote (
> Summary) explaining what the product does and who it serves. LLMs use this first to evaluate relevance. - Core Pages (H2 Section): A curated list of markdown links (
- [Title](URL): Description) leading to your primary value proposition, pricing, and feature overviews. - Documentation & Resources (Optional H2): Direct links to guides, OpenAPI specs, and SDK reference files so AI assistants can solve user coding questions with zero hallucination.
Frequently Asked Questions
What is llms.txt and why does my website need it?
llms.txt is an open proposal (RFC from llmstxt.org) that provides a clean, markdown-formatted summary of your website specifically designed for Large Language Models (LLMs) and AI agents like ChatGPT, Claude, Perplexity, and Cursor. Because LLMs have context window constraints and struggle with noisy HTML markup, client-side JavaScript, and cookie banners, llms.txt gives them structured canonical URLs and documentation in token-efficient plain text.
Where should I place the generated llms.txt and ai.txt files?
Place both files directly in your website's root public directory (e.g. public/llms.txt and public/ai.txt). When you deploy, they should be publicly accessible at https://yourdomain.com/llms.txt and https://yourdomain.com/ai.txt, exactly like robots.txt and sitemap.xml.
What is the difference between llms.txt and ai.txt?
llms.txt (from llmstxt.org) focuses on information architecture and document discovery—telling AI agents what your product does and which pages to read. In contrast, ai.txt (from AI Visibility) specifies legal and operational policies—such as whether AI models are allowed to train on your data, how AI assistants should format citations, and contact details for automated agents.
How does Answer Engine Optimization (AEO) help my product get cited by Perplexity and ChatGPT?
When users ask AI search engines questions like 'What is the best vector database for Rust?' or 'How do I audit SaaS costs?', the AI retrieves information from sources that provide concise, authoritative, and machine-readable context. By publishing a well-structured llms.txt and markdown discovery endpoints, you make it easy for AI crawlers to ground their answers in your exact facts and link directly to your product.
Do I need to maintain both a human website and an llms.txt file?
Yes. Your HTML pages serve human visitors, visual design, and interactive UI, while llms.txt acts as the machine-readable executive summary for AI search bots and developer agents. Advanced sites can also implement HTTP Accept: text/markdown content negotiation so AI agents requesting any HTML URL receive clean markdown automatically.
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