LLMs.txt for SEO: How to Help AI Understand Your Website

Intro

Large language models are no longer just “cool chatbots.” They’re where people are asking product questions, comparing tools, checking pricing, and researching decisions.

That means your website now has two primary audiences:

• Humans, arriving via classic search, social and direct

• AI systems, arriving via crawlers, connectors, IDEs, and AI search features

Traditional SEO still matters, but there’s a growing parallel discipline: making your content easy for AI to understand and reuse. That’s where the proposed llms.txt standard comes in.

For Ranktracker, we look at llms.txt as a small but useful piece of an AI-readiness checklist. It won’t replace your SEO work, but it can help align your site with the way LLMs actually consume web content.

Let’s dig into what it is, where it came from, and how to implement it in a way that makes sense for a real business site, not just a lab demo.

What is llms.txt, in plain English?

llms.txt is a plain-text (usually Markdown) file you place at the root of your domain, like:

https://yourdomain.com/llms.txt

Its job is simple: tell large language models where the “good stuff” is on your site.

Instead of letting an AI agent guess which pages matter, llms.txt provides a curated map of key URLs:

• documentation

• feature pages

• pricing and policies

• important guides and resources

• other LLM-friendly markdown files

It doesn’t replace robots.txt or sitemap.xml:

• robots.txt = “Here are the rules for crawling my site.”

• sitemap.xml = “Here’s a list of URLs you can index.”

• llms.txt = “Here’s the content that best represents who we are and what we do.”

Think of it as a short, opinionated guidebook that says: “If you’re an AI trying to explain this site, start here.”

Where did llms.txt come from – and who actually uses it?

The idea behind llms.txt was formalised in 2024 by Jeremy Howard (fast.ai / Answer.AI). The problem he was trying to solve:

• Websites are messy: navigation, ads, forms, JS, trackers, layout cruft.

• LLMs have limited context windows, so they can’t just slurp an entire site at once.

• Developers, tools and AI agents often want a clean, structured entry point into docs or product information.

The proposed solution: a standard file at /llms.txt that:

1. Describes the project or site in a short human/AI-readable way

2. Lists key markdown- or text-friendly resources

3. Optionally marks some URLs as “optional” if context is tight

Today, we’re seeing early adopters, especially in developer ecosystems and documentation-heavy projects, including:

• API and component libraries

• Documentation generators

• Some SaaS documentation sites

• A handful of agencies and SEO platforms experimenting with GEO (Generative Engine Optimization)

The important nuance:

• Major LLM providers (OpenAI, Anthropic, Google, etc.) have not publicly committed to honouring llms.txt in the same way search engines honour robots.txt.

• Some, like Anthropic and Nuxt UI, publish their own llms.txt files for others to use, but that doesn’t guarantee their crawlers consume it for their own models.

So right now, llms.txt is:

• A proposed standard, not a guaranteed ranking or retrieval signal

• Useful for tools and workflows that explicitly support it (e.g. IDEs, agents, AI-aware docs tools)

• A good “future-proofing” move for complex sites

You shouldn’t expect a traffic spike the day you add it. But you also don’t need to invest weeks of engineering time to do it properly.

How the llms.txt spec actually works

The proposed spec deliberately uses Markdown because it’s:

• Easy for humans to read

• Easy for LLMs to parse

• Structured enough for simple parsers and scripts

A valid llms.txt typically follows this structure:

1. H1 heading

Name of the project or site

2. Blockquote

A short description of what the site or product is

3. Optional detail paragraph(s)

A bit more context about how to interpret the links

4. One or more H2 sections

Each H2 groups a list of files or URLs

5. Within each H2, a bullet list of links

Each list item is a markdown link plus optional notes: [Link title](https://url): optional description

6. **Optional ## Optional section

Links here are considered lower priority and can be skipped when context is tight

Here’s a simplified example for a generic site:

# your-website.com

> Your Website is an online platform for X, Y, and Z, providing guides, tools, and documentation.

Your Website helps users do A, B, and C with step-by-step tutorials and product documentation.

## Docs
- [API Overview](https://your-website.com/docs/api-overview.md): Authentication, endpoints, rate limits, and example requests.
- [Quickstart](https://your-website.com/docs/quickstart.md): How to get up and running in 10 minutes.

## Policies
- [Terms of Service](https://your-website.com/terms.md): Legal terms and acceptable use.
- [Refund Policy](https://your-website.com/refund-policy.md): How refunds and cancellations work.

## Guides
- [Getting Started Guide](https://your-website.com/guides/getting-started.md): High-level walkthrough of core features.

## Optional
- [Company](https://your-website.com/about.md): Background, mission, and team.
- [Press](https://your-website.com/press.md): Press kit, logos, and media mentions.

Notice what this file does not try to do:

• It doesn’t list every blog post or landing page

• It doesn’t replace your sitemap

• It doesn’t contain crawl rules

It’s simply a curated directory of the content that would help any LLM explain your site to someone else.

A Ranktracker-flavoured llms.txt example

To make this real, here’s how a trimmed-down llms.txt could look for a platform like Ranktracker:

# ranktracker.com

> Ranktracker is an all-in-one SEO platform that helps marketers and agencies track keyword rankings, discover new keyword opportunities, audit technical issues, and monitor backlinks.

Ranktracker combines real-time SERP data, keyword intelligence, and site auditing into a single SaaS platform. Use the docs and guides below to understand how the tools work and how to apply them in day-to-day SEO.

## Core Tools
- [Rank Tracker](https://www.ranktracker.com/features/rank-tracker/): Setting up keyword tracking, locations, devices, and interpreting positions and visibility.
- [Keyword Finder](https://www.ranktracker.com/features/keyword-finder/): Keyword discovery workflows, difficulty scores, search intent, and SERP snapshots.
- [SERP Checker](https://www.ranktracker.com/features/serp-checker/): On-demand SERP analysis, competitor comparison, and localised results.
- [Web Audit](https://www.ranktracker.com/features/web-audit/): Technical SEO checks, error categories, and prioritising fixes.
- [Backlink Checker](https://www.ranktracker.com/features/backlink-checker/): Backlink discovery, authority metrics, and anchor analysis.
- [Backlink Monitor](https://www.ranktracker.com/features/backlink-monitor/): Monitoring new, lost, and changed backlinks over time.

## Guides & Education
- [SEO Guides](https://www.ranktracker.com/blog/): In-depth tutorials on SEO, AEO, GEO, and SERP strategies.
- [Ranktracker Academy](https://www.ranktracker.com/academy/): Structured courses for beginners and advanced SEO practitioners.

## Policies & Company
- [Pricing](https://www.ranktracker.com/pricing/): Plans, billing model, and usage limits.
- [Privacy Policy](https://www.ranktracker.com/privacy-policy/): Data handling, privacy, and compliance.
- [Terms of Service](https://www.ranktracker.com/terms-of-service/): Legal terms and acceptable use.

## Optional
- [About Ranktracker](https://www.ranktracker.com/about/): Company history, mission, and leadership.
- [Contact](https://www.ranktracker.com/contact/): Ways to reach the team.

Any AI agent or tool that understands llms.txt can now:

• Jump straight to the right docs when a user asks “How does Ranktracker’s Web Audit work?”

• Pull a clean, high-level description of the product

• Avoid outdated or fringe URLs that don’t represent the core offering

That’s the practical value.

Why llms.txt exists in an AI-first world

So why bother at all, if SEO and sitemaps already exist?

Because LLMs consume the web differently:

• They’re constrained by context window size. They can’t cram your entire website into memory at once.

• Raw HTML is noisy. Navigation, ads, sidebars and JS are irrelevant to understanding your value proposition.

• For coding and docs, people increasingly query AI inside IDEs, editors, and specialised tools. Those tools often want a single, clean, structured source of truth.

llms.txt is a way to say:

“If you only have limited space in your context window, these are the URLs you should load first.”

For developer docs, this is almost a no-brainer. For a marketing-heavy site, it’s more about future-proofing and ensuring your canonical explanations are easy to find.

llms.txt vs robots.txt vs sitemap.xml

It’s easy to confuse these three, so let’s draw a line between them.

robots.txt

• Lives at /robots.txt

• Sets rules like Allow and Disallow for specific user agents

• Used by search engines and some AI crawlers to honour your preferences

• Can block access to certain folders or files

sitemap.xml

• Usually lives at /sitemap.xml (and can reference other sitemaps)

• Lists indexable URLs and sometimes metadata (last modified, priority)

• Helps crawlers discover content efficiently

llms.txt

• Lives at /llms.txt

• Contains a curated list of important, LLM-friendly URLs

• Written in Markdown, not XML

• Offers context and structure rather than rules

robots.txt is about permissions. sitemap.xml is about coverage. llms.txt is about prioritisation and understanding.

They’re complementary, not replacements.

What llms.txt can realistically do for you today

Let’s be blunt:

• There is no solid evidence yet that llms.txt directly boosts traffic, rankings, or AI citation frequency.

• Major LLM providers have not announced official support in the way search engines did for sitemaps.

So why bother?

Because it’s a low-effort, low-risk hygiene task that can:

• Make your site easier to integrate into AI-first tools (IDE plugins, agents, AI search products that explicitly use llms.txt).

• Make it trivial for teams internally to point AI assistants (like ChatGPT or Claude) at canonical documentation:

“Answer only using the docs linked from https://example.com/llms.txt.”

• Give you a head start if and when llms.txt or something like it becomes part of a wider GEO / LLMO standard.

Think of it like adding structured data before rich results were everywhere. Early adopters didn’t always see instant return, but they were in a much better position when usage ramped up.

Where llms.txt makes the most sense right now

For some websites, llms.txt is almost overkill. For others, it’s extremely useful already.

It makes the most sense when:

• You have a complex product with lots of features and modes

• You maintain developer documentation (APIs, SDKs, components, integrations)

• Your site covers a large information space (universities, big content libraries, regulatory/legislative hubs)

• You expect users to ask AI about your product from inside tools (IDE, editor, CLI, etc.)

Examples:

• A SaaS platform with separate docs for API, dashboard, webhooks, and integrations

• An SEO platform (like Ranktracker) with multiple modules, help centres, and in-depth guides

• A hosting provider with knowledge-base articles, tutorials, and platform-specific workflows

For a small brochure site with five pages, llms.txt is still easy to add, but you’ll feel less impact because everything is already simple.

Step-by-step: how to create an llms.txt file for your site

You don’t need a special plugin or AI agent to do this well. Here’s a practical workflow.

1. Decide what counts as “canonical”

Start by answering:

• Which pages explain our core product or service?

• Which docs or guides do we wish AI always used as references?

• Which policies or legal pages should never be misrepresented?

• Which pages are outdated or noisy and should not be surfaced?

On a large site, aim for dozens or low hundreds of URLs, not thousands.

2. Group URLs into logical sections

Create a rough structure like:

• ## Product Docs

• ## Getting Started

• ## Pricing & Policies

• ## Guides & Education

• ## Optional

This matches how both humans and AIs think about your content.

3. Write the llms.txt content in Markdown

Follow the spec:

1. H1 with your site or project name

2. Blockquote with a crisp summary (1–3 sentences)

3. A short paragraph of extra context

4. H2 sections with bullet lists of [Title](URL): description

5. An ## Optional section for nice-to-have links

Keep descriptions:

• Short and informative

• Free of fluff and marketing buzzwords

• Focused on what the user will learn or achieve

4. Save and upload it to your root directory

• Save the file as llms.txt (UTF-8 encoding)

• Upload it to your site’s root (/), alongside robots.txt and potentially sitemap.xml

• Confirm you can access https://yourdomain.com/llms.txt in a browser

5. Optionally, use a generator or CMS integration

If you run on WordPress, Drupal, docs tooling, or a modern static site generator, you may find:

• Plugins that generate llms.txt automatically from your navigation or docs

• Documentation builders that can output both HTML and .md versions of pages, plus a matching llms.txt

Automatic tools are helpful, but you should still curate and edit the file. The value lies in opinionated prioritisation, not just dumping your menu structure.

llms.txt, SEO, AEO, GEO, and LLMO: how does it all tie together?

There are a lot of acronyms flying around:

• SEO – classic search engine optimisation

• AEO – answer engine optimisation (optimising to appear in AI answers and overviews)

• GEO – generative engine optimisation (optimising content for generative AI systems)

• LLMO – optimising for LLM-based discovery and brand mentions

Where does llms.txt fit?

It’s one of the technical enablers for AEO/GEO:

• SEO and content still do the heavy lifting (topics, authority, links, intent coverage).

• Structured data, clean information architecture, and strong entities make your content easier to understand.

• llms.txt adds a machine-readable index of your most important pages, tuned specifically for AI agents instead of web crawlers.

For Ranktracker’s audience, a sensible mental model is:

SEO gets you discovered. 

AEO/GEO helps AI explain you correctly. llms.txt is one of the small, technical tools you can use to support that.

Monitoring and maintaining your llms.txt

Once you publish it, treat llms.txt like any other part of your technical setup.

Things to keep an eye on:

• Accessibility: Can https://yourdomain.com/llms.txt be loaded without redirect loops, auth, or 404s?

• Server logs / analytics:

  • Do you see hits to /llms.txt from AI-related user agents over time?

  • Are developer tools or agents in your ecosystem referencing it?

• Content drift:

  • When you launch a major new feature or retire an old one, update the file.

  • When URLs change (migrations, new docs structure), keep the links fresh.

• Conflicts:

  • Ensure llms.txt doesn’t point to content blocked by robots.txt

  • Make sure descriptions align with what’s actually on the page

From a Ranktracker perspective, you can also:

• Use Rank Tracker to monitor branded queries likely to interact with AI answers (e.g. “[product] review”, “how to use [feature]”, “[brand] pricing”).

• Use Keyword Finder to uncover “AI-flavoured” queries people actually type, such as “how to show up in AI search” or “llms.txt example”.

• Use SERP Checker to see when and where AI overviews or answer-type results appear for your target keywords, then watch how visibility changes over time.

You won’t be able to attribute changes solely to llms.txt, but you’ll at least have data around how your overall AI-focused optimisation is performing.

So… should you implement llms.txt now?

The honest answer is:

• If you’re expecting an instant rankings boost, you’ll be disappointed.

• If you want your site to be easier for AI agents, tools, and future crawlers to reason about, it’s worth the hour or two it takes to set up properly.

For:

• Complex SaaS platforms

• Developer documentation

• Large knowledge bases

• Brands investing heavily in AEO/GEO

llms.txt is a sensible, low-friction addition to your stack.

For smaller sites, it’s more of a nice-to-have than a necessity, but still easy enough that it’s worth doing once and then revisiting occasionally.

In other words: treat llms.txt like you treated structured data in the early days. Not the core of your strategy, but a smart way to be ready for where AI search is heading.