How to Create an llms.txt File for Your Website
Contents
An llms.txt file is a plain-text Markdown file you place at your website's root (yoursite.com/llms.txt). It has one required section, an H1 with your project name, plus an optional summary and H2-grouped links to your most important pages. Write it in a text editor, upload it to your root directory, and update it as your site changes.
How Is an llms.txt File Different From robots.txt and a Sitemap?
An llms.txt file, a robots.txt file, and a sitemap.xml file solve three different problems. llms.txt hands AI models a curated summary of your best content, robots.txt tells crawlers what they may or may not access, and sitemap.xml lists every indexable URL on your site for search engines. None of the three overlaps completely with another, which is why most sites end up running all three at once.
| File | Purpose | Audience | Controls access? |
|---|---|---|---|
| llms.txt | Curated summary and links to your most important pages, written for AI models | LLMs and AI assistants (ChatGPT, Claude, Perplexity, Gemini) | No |
| robots.txt | Rules for which crawlers can or cannot access parts of your site | Search engine and AI crawlers, as a directive | Yes |
| sitemap.xml | Complete, machine-readable list of every indexable URL | Search engine crawlers | No |
Neither robots.txt nor sitemap.xml was designed with language models in mind. robots.txt only blocks or allows access, it does not explain what your content means or which pages matter most. sitemap.xml lists URLs but carries no context about priority or purpose. llms.txt fills that specific gap: it is the only one of the three written as a short, human-readable explanation of what your site is and what an AI system should read first.
What Do You Need Before You Create an llms.txt File?
Before you write a single line, you need two things: a short list of canonical pages worth surfacing to an AI system, and access to your site's root directory. Skipping either step usually produces a file that is either empty or unusable.
Start by listing the content you would want an AI assistant to read first if it only had time for a handful of pages: your documentation, your flagship product or service pages, your blog or changelog, and any page that answers the questions your users ask most. If you want the full background on what an llms.txt file actually is and why it exists, that companion piece covers the origin of the format in more depth.
You will also need root-level access to your site, either through FTP, your hosting provider's file manager, or your site's codebase if it is self-hosted. Without that access, you cannot place the file at yoursite.com/llms.txt, which is the location the format expects.
It's also worth deciding what to leave out. Pages behind a login, paywalled content, and internal admin tools do not belong in an llms.txt file, since an AI crawler cannot access them any more than a human visitor without credentials. A shorter, accurate list of five to ten pages is more useful to an AI system than a long list padded with links it cannot actually read.
What Is the Correct Format for an llms.txt File?
The correct format comes directly from the original llms.txt specification, proposed by Jeremy Howard and published on September 3, 2024 (source: llmstxt.org). It defines a single required element, an H1 heading with your site or project name, followed by three optional elements: a blockquote summary, free-text context paragraphs, and H2-grouped sections of links.
Each link inside an H2 section follows a simple pattern: [name](url): description. The name is the page title, the url is the full or relative link, and the description is a short, plain sentence explaining what a reader (or an AI system) will find there. There is no strict limit on how many H2 sections or links you include, but the spec is built around brevity, not exhaustiveness.
A Minimal Working Example
A short, fictional example makes the structure easier to picture than a bare description:
# Acme Docs
> Acme Docs is the documentation site for Acme's API platform, covering authentication, endpoints, and integration guides.
## Docs
- [Getting Started](https://docs.acme.com/getting-started): Setup steps for a new Acme account and API key.
- [Authentication](https://docs.acme.com/auth): How to generate and rotate API tokens.
## Guides
- [Webhooks](https://docs.acme.com/guides/webhooks): Configuring event notifications for account activity.
This example follows the required H1, an optional summary line, and two H2 sections grouping related links with one-line descriptions each. For more worked examples across different site types, see our collection of real llms.txt examples you can copy.
How Do You Write an llms.txt File Step by Step?
Writing an llms.txt file manually takes five steps, and none of them require a generator tool or a developer.
- List your canonical pages. Pull together the handful of pages that best represent what your site or product does.
- Draft the file in a plain text editor. Any text editor works; the file is Markdown, not code.
- Order sections by priority. Put your most important content, usually documentation or your core product pages, in the first H2 sections.
- Write a one-line description for each link. Keep each description factual and specific, not marketing copy.
- Save the file as
llms.txt. No extension changes, no capital letters, exactly that filename.
Most site owners finish all five steps in under an hour for a first version, even for a site with dozens of pages, since the file only needs to reference a handful of them. Once the file is written, the remaining work is placement and verification, covered next.
Where Should You Upload Your llms.txt File, and How Do You Verify It?
Your llms.txt file belongs at your site's root path, so it is reachable at yoursite.com/llms.txt. Documentation-heavy sites sometimes also place a secondary copy at a docs subpath, such as yoursite.com/docs/llms.txt, but the root location is what the specification and most AI crawlers expect by default.
To verify the file is live, open the URL directly in a browser and confirm the raw Markdown displays correctly, with no formatting errors or broken links. If you prefer a command-line check, run curl -I https://yoursite.com/llms.txt and confirm the response returns a 200 status code. Either method takes under a minute and confirms the file is both reachable and not accidentally blocked by a redirect or a robots rule.
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Try mentionLABShould You Also Create an llms-full.txt File?
An llms-full.txt file is a companion to llms.txt, containing the complete text of your key pages in one file instead of just links and short descriptions. Where llms.txt is a curated index, llms-full.txt is the full content itself, assembled so an AI system can read everything in a single request.
The trade-off is size. A full-content export can balloon quickly on a large documentation site, and because language models process text within a limited context window, an oversized llms-full.txt file may never be read in full even if it is technically present. Treat llms-full.txt as optional and situational, useful for smaller documentation sets, riskier as a blanket recommendation for large sites with hundreds of pages. If your documentation is small, say under a few dozen pages, the size risk is minor and llms-full.txt can be a genuine convenience for an AI system that wants full context in one fetch.
Does an llms.txt File Actually Improve Google Rankings or AI Citations?
Google says llms.txt has no effect on Search rankings, and an independent 10-site study found the same for AI citations. Both points matter more than any generator tool's marketing copy, because they come from a primary source and a measured study rather than an assumption.
AI Overviews are not a fringe feature to weigh this against. Google's AI Overviews reached over 2.5 billion monthly users by Google I/O 2026, up from roughly 2 billion the year before (source: CNBC, May 19, 2026). That scale is exactly why the honest answer on llms.txt matters: a lot of visibility is genuinely at stake, which makes it worth getting the facts right rather than assuming a small text file solves the problem.
On the ranking question specifically, Google's own AI-optimization documentation states that no special file such as llms.txt is required or beneficial for appearing in generative or classic search results; it creates neither a ranking boost nor a penalty (source: Google Search Central, developers.google.com/search/docs/fundamentals/ai-optimization-guide).
Independent measurement backs that up. A tracking study across 10 sites in finance, SaaS, e-commerce, insurance, and pet care, following 90 days before and 90 days after implementation, found that 8 of 10 sites saw no traffic change attributable to adding an llms.txt file alone (source: Search Engine Land, published January 20, 2026). The study's conclusion was that time is better spent on structured data, FAQ content, technical fixes, and press relationships than on the file by itself.
There is one place llms.txt does matter today: compatibility checks. Chrome Lighthouse added an Agentic Browsing audit category in Lighthouse 13.3, shipped by default since May 7, 2026, which checks whether a site has an llms.txt file at its root (source: Chrome for Developers, corroborated by Search Engine Land, May 20, 2026). That check does not measure ranking impact; it measures whether an AI agent browsing your site on a user's behalf can find a machine-readable summary of it.
Put together, an llms.txt file is a low-effort, low-risk addition, not a growth lever on its own. It works best alongside structured data that helps machines understand your content and a broader plan for citation-worthy content, not as a replacement for either. For that wider strategy, see the broader strategy for getting your content cited by AI. In practice, that means llms.txt belongs on a launch checklist, not at the top of a priority list above content and technical fundamentals.
How Often Should You Update Your llms.txt File?
Update your llms.txt file whenever you add a major new section, restructure your site, or launch content significant enough that an AI system reading your site would need to know about it. There is no fixed schedule required by the specification.
Treat it the way you would treat a lightweight sitemap: not something you write once and forget, but not something that needs weekly attention either. A quarterly review is a reasonable default for most sites, with an off-cycle update any time you ship a major new product page, documentation section, or content pillar.
Frequently Asked Questions About llms.txt
Does Google use llms.txt for search rankings? No. Google's own documentation states that no special file such as llms.txt is required or provides a ranking benefit for appearing in generative or classic search results (source: Google Search Central).
What is the difference between llms.txt and llms-full.txt? llms.txt is a short, curated index of links with one-line descriptions. llms-full.txt contains the full text of those same pages in a single file, which is more complete but can grow too large for a language model to process in one pass.
Do you need a developer to create an llms.txt file? No. The file is plain-text Markdown, written in any text editor. Uploading it only requires root-level access to your site through FTP or your hosting provider's file manager.
How often should you update your llms.txt file? Update it after major content additions or structural changes to your site. A quarterly review is a reasonable baseline, with off-cycle updates whenever you launch a significant new section.
Does Chrome Lighthouse check for an llms.txt file? Yes. Lighthouse 13.3, shipped by default since May 7, 2026, added an Agentic Browsing audit category that checks whether a site has an llms.txt file at its root (source: Chrome for Developers).
An llms.txt file is a small, low-risk piece of a much larger picture: making a site genuinely readable by both search engines and AI systems. If you want to know where your own site stands, beyond a single file, on structured data, indexation, and content structure, that is closer to what a full GEO audit is built to answer, including how the pieces fit together as generative engine optimization as a whole.
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