A GEO Checklist for B2B Sites: robots.txt, llms.txt, Schema and Citability
What actually gets a site cited by AI search engines, and which popular advice is still just a hypothesis
Short answer: a B2B site gets cited by AI search engines when three things are true at once. AI crawlers can fetch the content and the site is indexed; the content is machine-readable (server-rendered HTML and consistent structured data); and every page gives an answer that can be lifted out verbatim. There is no requirement for special "AI markup", a particular text length, or an llms.txt file.
Generative Engine Optimization (GEO) isn't a new profession or a new list of rules. The foundation is the same as ordinary search. But many sites with solid SEO still miss a few of the points below, usually without anyone noticing. A misconfigured robots.txt, or a company name spelled three different ways, can be enough for a model to pick a competitor as its source.
Requirement, method or hypothesis?
GEO advice mixes three different kinds of claims. Keep them apart:
| Category | Meaning | Checks |
|---|---|---|
| Documented requirement | The search engines describe it in their own docs. Google says AI Overviews and AI Mode use the regular index, need no special AI optimisation, and require pages to be indexable and snippet-eligible. | 1, 2, 5 (for rich results), 11 |
| Working method | Not required, but formats that in practice recur in what gets cited, overlapping with Google's advice on useful content | 6, 7, 8, 9, 10, 12 |
| Hypothesis | Conventions AI companies haven't confirmed they use. Low cost, unclear effect. | 3, 4 |
Crawlability
1. Explicit AI crawler rules in robots.txt. Training crawlers (e.g. GPTBot, Google-Extended) collect data for future models; search/fetch crawlers (OAI-SearchBot, ChatGPT-User, PerplexityBot) retrieve pages that can be cited right now; Bingbot feeds the Bing index that Copilot builds on. If you want to appear in AI answers, the search crawlers must get in. ClaudeBot handles crawling for Claude. Also check your firewall and CDN: a WAF rule returning 403 to an unfamiliar user agent never shows up in an SEO report. Look for 403/429 responses in server logs.
2. Be in Google's and Bing's index, and allow snippets. Google's AI features need an indexed page that's eligible for a snippet and not restricted by nosnippet or a low max-snippet. Many teams have never opened Bing Webmaster Tools, even though ChatGPT search has leaned on Bing's index and Copilot is built on it. Verify the domain, submit the sitemap and compare site: counts.
llms.txt (hypothesis)
llms.txt is a proposed standard (llmstxt.org) for a root-level Markdown file describing a site for language models. Be clear about what's known: Google has said it doesn't use it as a search signal, and OpenAI, Anthropic and Perplexity haven't documented that their crawlers read it. The case for it is low cost when generated automatically, some tools and agents fetch it, and writing it forces you to define what the site is.
3. Structure it correctly: an H1 with the site name, a blockquote summary, optional context paragraphs, H2 sections with - [Title](URL): description lists, and an Optional section. A curated short list beats hundreds of URLs.
4. Generate it automatically. llms-full.txt holds the full content of linked pages as Markdown. Hand-maintained files go stale, so build both into your publishing pipeline: when an article is published, it appears in the next build.
Structured data that builds entities
5. Organization, Person and Article/BlogPosting as JSON-LD in <head>, with datePublished and dateModified matching the visible dates. Organization gets sameAs links to profiles; Person gets jobTitle, worksFor and a LinkedIn sameAs.
6. FAQPage, BreadcrumbList and stable @ids. Give the organisation a fixed id like https://www.example.com/#organization and each author their own, then reference the same ids from publisher, author and worksFor on every page. One entity each, not twenty partial copies. Only mark up FAQs that are visible on the page.
Citable content (methods)
7. A short answer first — two or three sentences under the H1 that hold up out of context — and one clear definition per page.
8. Question headings, Q&A sections, tables and sourced figures. If a figure has no source, label it as experience or as a clearly marked example rather than guessing. Producing this consistently at scale is a content-operations problem; Successifier covers it in its guide to AI-driven content marketing for B2B (in Swedish).
Entity consistency and freshness
9. Same company everywhere. Compare name, one-line description, location and category across your About page, LinkedIn, directories and business profiles, and fix every mismatch. Add real author pages; they're also the home of your Person schema.
10. Freshness. Show honest update dates, run a quarterly review of your key pages, set sitemap lastmod from the same field as dateModified (not build time), and enable IndexNow. If every deploy bumps every lastmod, the signal becomes worthless.
Technical foundation and measurement
11. Self-referencing canonicals, hreflang for language versions, green Core Web Vitals, descriptive alt text and, critically, server-rendered HTML. Content that only exists after JavaScript runs is invisible to several AI crawlers. Test with curl. Most of this overlaps with classic technical SEO, covered in SEO for B2B companies (in Swedish).
12. Measure per engine. Run a fixed list of buyer prompts monthly in ChatGPT, Perplexity, Gemini and Copilot; segment GA4 referrals from AI domains; and track mention rate over time with a dedicated tool. Prompt testing is described in AI visibility in marketing (in Swedish).
Where to start
Checks 1, 2 and 11 are the documented requirements, they block everything else, and they can be verified in an afternoon. Then do structured data in a sprint and build the content format into your editorial routine. Add llms.txt if it can be generated automatically, but don't let it get in the way of the rest.
Originally published at https://www.successifier.se/blog/geo-checklista-for-b2b-sajter-2026-llms-txt-schema-och-citerbarhet (in Swedish)
Top comments (1)
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