llms.txt -The File That Separates 63 from 34

llms.txt is a plain-text file sitting at your domain root (e.g., example.com/llms.txt) that gives large language models a structured summary of your website.

Think of it as robots.txt's smarter cousin. robots.txt tells crawlers which pages to access. llms.txt tells AI systems what your site actually is, what it offers, and how to navigate it.

Tidio's llms.txt runs 251 lines. It lists every product, every feature, every integration. When ChatGPT needs to answer "What live chat tools support Shopify?" -Tidio's file hands over the answer on a silver platter. Crisp? No llms.txt at all. Score: 34.

The format is dead simple: - A brief business description - Key content areas with URLs - Product/service categories - Contact info and location - Links to important resources (FAQ, docs, API references)

Here's what happens without llms.txt. Someone asks ChatGPT about your industry. The AI has to piece together your site's purpose from scattered HTML pages, marketing fluff, and cookie banners. It gets confused. It skips you.

Put on ChatGPT's glasses for a second. It's scanning hundreds of sites for an answer. One site has a clear, structured summary of everything it does. Another site forces the AI to parse fifty pages of JavaScript-heavy marketing copy. Which one gets cited?

We've audited sites across multiple verticals. The pattern is unmistakable: - Sites with llms.txt get their business described accurately by AI -because they wrote the description themselves - Sites without it get described wrong, or worse, not described at all - The file works from day one -unlike SEO authority that takes months to build - You control the narrative. You define how AI systems talk about your business.

Create a file called llms.txt in your site's root directory. Here's the skeleton:

``` # Example Business Name

> Brief one-line description of what the business does.

## About Two to three sentences about the business, its expertise, and what makes it unique.

## Products & Services - Category 1: Description (URL: /category-1) - Category 2: Description (URL: /category-2)

## Key Content - Blog: Expert articles about [topic] (/blog) - FAQ: Common questions answered (/faq) - Guides: In-depth resources (/guides)

## Contact - Location: City, State - Email: hello@example.com - Website: example.com ```

Want to go deeper? Create llms-full.txt with your complete content inventory, taxonomy, and technical specs. Our own llms-full.txt runs the full content map -every article, every audit, every tool.

For Shopify: upload via the theme editor (Settings > Files) or host on your CDN. For WordPress: drop it in the root directory or use a plugin. For Next.js or static sites: add it to your public folder.

Start here: Open a text editor right now and write 10 lines describing your business. That's your llms.txt draft.

We see the same mistakes in audit after audit:

Writing a novel instead of a summary. AI systems want concise, structured facts -not your brand manifesto. Tidio's 251 lines work because every line is specific product information, not fluff.

Never updating it. Your llms.txt from six months ago doesn't mention your three new features. AI is now giving outdated info about your business.

Writing marketing copy. "We're the world's leading provider of synergistic solutions..." -AI systems want facts. What do you do. Where are you. What do you sell. Period.

Forgetting URLs. The file should help AI navigate to specific pages. A description without links is a map without roads.

Putting it in a subdirectory. It must live at /llms.txt. Not /assets/llms.txt. Not /docs/llms.txt. The root.

The llms.txt criterion carries 3% weight in the Technical Plumbing tier of the AEO scoring model. That might sound small, but the downstream effects are outsized because llms.txt shapes how AI understands every other page on your site.

Sites with a well-structured llms.txt consistently score 7-8/10 on this criterion. Sites without one score 0 - there's no partial credit. You either have the file or you don't. In the live chat vertical, Tidio's 251-line llms.txt contributes to its 63/100 overall score. Crisp, with no llms.txt at all, sits at 34/100. That 29-point gap isn't caused by llms.txt alone, but when we break down the scoring, the file's presence correlates with higher scores across multiple criteria because it helps AI contextualize everything else on the site.

Across the 500+ sites we've audited, fewer than 15% have an llms.txt file. The adoption rate among Y Combinator startups is higher - roughly 25% - but still leaves massive ground unclaimed. Early adopters get disproportionate benefit because AI systems are actively looking for this file and rewarding the sites that provide it.

Each AI engine processes llms.txt slightly differently, but the core behavior is the same: they check your domain root for the file and use it as a primary context source.

ChatGPT (GPTBot) fetches /llms.txt early in its crawl cycle. When it finds a structured summary with clear product descriptions and URLs, it uses those descriptions almost verbatim when answering questions about your business. Without the file, GPTBot has to infer your business purpose from scattered page content - and it frequently gets it wrong or skips you entirely.

Claude (Anthropic's crawler) treats llms.txt as a trust signal. A site that takes the time to create a machine-readable summary demonstrates intentionality about AI engagement. Claude's retrieval system uses the file to build an entity model - what the business does, what it offers, where its key content lives. This entity model feeds directly into citation decisions.

Perplexity is the most aggressive consumer of llms.txt. When Perplexity builds its source list for an answer, it checks llms.txt to quickly determine whether a site is relevant to the query. A site with a clear, structured description gets evaluated faster and more accurately. Sites without the file require Perplexity to scan multiple pages to determine relevance - and with its speed-optimized architecture, it often moves on before completing that scan.

Google's AI Overviews don't directly consume llms.txt the way purpose-built AI crawlers do, but the file's content reinforces the same signals Google already parses from structured data and meta descriptions.