What is an llms.txt file and should my hotel have one?

llms.txt is a plain text file placed at the root of your website (yourdomain.com/llms.txt) that tells AI language models how to understand and describe your property. It is the hospitality equivalent of a press kit written for robots: a clean, authoritative summary of what your hotel or rental is, where it is, who it's for, and what makes it worth recommending. AI systems like Perplexity and ChatGPT with browsing will read this file when they crawl your site, and may use it directly when generating travel recommendations.

What is the earliest measurable effect of publishing an llms.txt file?

Improved accuracy in how AI describes your property: fewer vague or incorrect descriptions and more specific attribute mentions, ahead of any change in how often you are recommended.

What is llms.txt and why does your hotel need one?

Q: Can you add an llms.txt file if you use Squarespace, Wix or Webflow?

Yes. Check the site builder's settings for adding files to the site root, or ask your website developer to add it; the file itself is the same plain text regardless of platform.

What problem does llms.txt actually solve?

llms.txt gives an AI system a clean, authoritative source to start from, instead of leaving it to extract your property’s actual information from a mix of navigation, booking widgets, photo galleries, marketing copy, review widgets and cookie banners.

AI systems are good at extracting meaning from messy content, but they perform better when they have that clean source: a simple text file that tells the AI, upfront, exactly what it needs to know about your property.

What does a filled-in hotel llms.txt look like?

A good hotel llms.txt file contains five things: property name and category, a short plain-prose description, key attributes, nearby landmarks and transport, and links to your most useful pages.

1. Property name and category. One line: The Harbour House Hotel: a 24-room boutique hotel in Porto, Portugal.

2. A 2-4 sentence description. Plain prose, no marketing superlatives. Describe the property type, location (neighbourhood and nearest landmark), what makes it distinctive, and who it’s right for. This is what the AI may use word-for-word in a recommendation.

Example:

The Harbour House Hotel is a 24-room boutique hotel in Porto's Ribeira district, 
facing the Douro river. Originally an 18th-century merchant's house, it has been 
a hotel since 1987. It is particularly suitable for couples and solo travellers 
who want a historic property with walkable access to Porto's main sights. 
The nearest metro station (São Bento) is a 6-minute walk.

3. Key attributes, listed. Things that match specific traveller queries:

Amenities: restaurant, bar, rooftop terrace, free WiFi, no pool, no parking
Room types: double rooms (18), suites (6)
Price range: €120-280 per night
Languages: Portuguese, English, Spanish, French
Pet policy: no pets
Check-in: 15:00, Check-out: 11:00

4. Nearby landmarks and transport. This powers location-based queries:

Location details: Ribeira district, Porto. 
Walking distance: São Bento station (6 min), Porto Cathedral (8 min), 
Luis I Bridge (4 min), Clérigos Tower (12 min).
Airport: Francisco Sá Carneiro Airport, approximately 20 minutes by taxi.

5. Links to your most useful pages for AI systems that can follow links:

Full property description: /about/
Room types and rates: /rooms/
Guest FAQ: /faq/
Location and directions: /location/

How do you create and deploy an llms.txt file?

Create a plain text file with a .txt extension, using clear headings and simple formatting (# Heading, - list item, no HTML), then upload it to the root of your website so it’s accessible at yourdomain.com/llms.txt. The whole process takes 30-60 minutes.

If you use WordPress, upload via your hosting file manager or FTP. If you use a site builder (Squarespace, Wix, Webflow), check their settings for adding files to the site root, or ask your website developer to add it.

Does an llms.txt file work immediately?

Not immediately in most cases: AI systems that browse the web in real time (Perplexity, ChatGPT with browsing) will read your llms.txt file the next time they crawl your site, which for Perplexity can happen within days of the file going live. For ChatGPT’s training data, the effect takes longer, as it depends on when the next training data collection run happens.

The earliest measurable effect is improved accuracy in how AI describes your property: fewer vague or incorrect descriptions, more specific attribute mentions.