How to make your website ready for AI chatbots and AI search
Six steps, in order, to let AI assistants, search engines and support chatbots read your site: crawler access, sitemaps, page text, schema and llms.txt.
By the Paperlink AI teamPublished 8 min read
Short answer
Let the crawlers you want read your pages, make every important page findable in a sitemap, and make sure the text is in the HTML the server sends. Then state your key facts in structured data and an llms.txt file, and write pages that put a specific answer first.
Three kinds of software now read your website besides people and search engines. AI assistants fetch pages so they can answer a question and link the source. AI companies collect pages to train models. Support chatbots import your help center so they can answer your customers. All three fail in the same few places, and you can check each place with a free tool in about an hour. This guide puts the checks in order and tells you when a check is done.
What "ready for AI" means
A machine can use a page only when four things are true. Each one depends on the one before it.
| Condition | The question a crawler asks | Where the answer lives |
|---|---|---|
| Permission | Am I allowed to read this path? | robots.txt |
| Discovery | Which pages exist, and which changed? | sitemap.xml, internal links, llms.txt |
| Readable text | Is the text in the HTML that the server sends? | Server-side rendering or static pages |
| Clear meaning | What is this business, and what does this page answer? | Headings, the first paragraph, structured data |
The first and third rows can stop a crawler completely. A copied robots.txt blocks the wrong crawler, or a page builds its text in the browser and arrives empty. Fix those before you spend time on the rest.
Step 1: Get a baseline score
Start with the AI readiness grader. It runs 8 checks on your home page and the files at the root of your host, and gives a score from 0 to 100. Write the score down, with the date. The score is not a goal in itself. Its value is the list of failed checks, sorted by the points that each fix wins back.
Grade every host that visitors use. Your marketing site, your docs subdomain and your help center platform are three different hosts. Each one has its own robots.txt and often its own sitemap, so each one can fail on its own.
Step 2: Decide which crawlers may read your site
Make a decision first, then write the rules. Ask one question for each kind of crawler: do you want this crawler to read your public pages?
- Search engines: almost always yes.
- AI search and user crawlers, which fetch a page so an assistant can answer from it and link it: yes, if you want assistants to describe your product from your own pages.
- AI training crawlers, which collect text for future models: your choice. Blocking them does not stop assistants from citing you, as long as the search crawlers can still read your pages.
Test your live file with the robots.txt checker. It shows, for 12 search and AI crawlers, whether each one may read your home page and a path you enter. If the result is not what you decided, write a new file with the robots.txt generator, which has presets for each of the three choices above. Then test again: the check is done when the table matches your decision for your help or docs path, not only for the home page.
Step 3: Make every important page findable
A crawler that may read your site still has to find the pages. A sitemap is the list it starts from. Run the sitemap checker on each host and look at two things: the number of URLs, and whether your help or docs pages are in the list. A sitemap that lists 40 blog posts and no help articles tells crawlers that your help center does not exist.
If a host has no sitemap, or the sitemap is clearly incomplete, the sitemap generator crawls a small site or one section and writes one. For a large site, ask your CMS or build step to generate it, so it changes when your pages change.
When your docs live on a separate platform, list both sitemaps in the robots.txt of your main site. One file can carry more than one Sitemap: line. Our own robots.txt on paperlinkai.com lists two: one for the website and one for the docs.
Step 4: Check what a crawler actually reads
What you see in a browser is not always what a crawler gets. Many AI crawlers read the HTML as the server sends it and do not run JavaScript. To see your page the way they do, put three important pages through the website text extractor: your pricing page, your most visited help article and one product page. Compare the result with the page in your browser. A section that is missing from the extracted text is built in the browser, and those crawlers miss it too.
Then test the meaning, not only the text. Run the same pages through the website summarizer. It writes a summary from the page text only. If the summary of your pricing page does not contain your prices, or the summary of a help article misses its main instruction, an AI assistant will probably miss them too. The usual fix is editorial: move the key fact into the first paragraph, under a heading that names it.
Step 5: State the basic facts as structured data
Structured data is a short JSON-LD script that states facts in a fixed format: your business name, address, logo, official profiles, or the questions and answers on a page. Search engines read it, and assistants that browse can use it to confirm facts that the layout hides.
- Add Organization (or LocalBusiness) markup to your home page with the schema markup generator. This is the one block that almost every site needs.
- If you have an FAQ page, mark it up with the FAQ schema generator. The markup must match the questions that visitors can see on the page, word for word.
Do not mark up facts that are not on the page, and keep the markup in step with the page when a price or address changes. Wrong structured data is worse than none.
Step 6: Publish a short map for AI tools
An llms.txt file is a Markdown list of your most useful pages, at /llms.txt. It is a proposal, not a standard. Some AI tools read it, and search engines have said that they do not use it for ranking. It is cheap to publish, and the work of choosing the pages is useful anyway. Draft one with the llms.txt generator, then edit the summary so it states facts, not slogans. Do this step last: a map is only useful when the pages it points to load and can be read.
Write pages that answer questions
The technical steps remove the reasons a machine cannot read you. They do not make your pages worth quoting. Assistants and support chatbots quote passages, so write passages that can be quoted:
- Answer first. Put the direct answer in the first two or three sentences under each heading.
- One question per heading. "How long do refunds take?" is a better heading than "Refunds".
- Specific facts. Numbers, dates, limits and conditions. "Refunds reach your card in 5 to 10 business days" can be quoted. "Refunds are fast" cannot.
- The same fact everywhere. If your pricing page and a help article give two different limits, a machine can quote either one.
To find sentences that are too long to quote safely, paste an article into the readability checker.
How a support chatbot reads your site
A support chatbot that imports your website needs the same four conditions. Paperlink AI is one example. It imports only public pages under the folder of the address you give. It reads your sitemap first and follows links (up to 5 steps on paid plans) only when the sitemap lists none of those pages. It also follows your robots.txt. It renders a limited number of JavaScript pages each day, and it does not import PDFs that your pages link to, so those go in as uploads. The website import guide has the details, and our guide on turning a help center into an AI chatbot walks through the setup.
The one-hour checklist
| Task | Tool | Done when |
|---|---|---|
| Baseline score for each host | AI readiness grader | You have a score and a dated list of failed checks |
| Crawler permissions | robots.txt checker and generator | Each crawler's result matches your decision, for your help path too |
| Sitemap | Sitemap checker or generator | Help and docs pages are listed, and robots.txt lists every sitemap |
| Text in the HTML | Website text extractor | Three key pages come out complete |
| Main point readable | Website summarizer | Each summary contains the page's key fact |
| Structured data | Schema markup and FAQ schema generators | Organization markup on the home page; FAQ markup matches the visible FAQ |
| AI map | llms.txt generator | /llms.txt loads as text and every link in it works |
Questions people ask
Is this different from normal SEO?
Mostly no. Crawler access, sitemaps, server-rendered text and structured data have been SEO basics for years. The new parts are the AI crawler tokens in robots.txt and llms.txt. The writing advice is the same for search snippets and AI answers: specific facts, answer first.
Will these steps get my site cited by AI assistants?
Not on their own. They remove the technical reasons that an assistant cannot read you. Being cited also depends on whether your pages answer the question well and whether other sites mention you.
How often should I check again?
After every redesign, CMS change or robots.txt edit, and once a quarter otherwise. A site change that moves text into JavaScript, or a new robots.txt copied from a template, can undo the work without anyone noticing.