Free AEO Checker
Answer engine optimization starts with six things AI engines look for on your site. See what a readiness check covers, then get your brand's AI visibility report.
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An AEO checker reviews the six site-level signals AI engines rely on before they can cite a site: structured data, FAQ markup, heading structure, AI bot access in robots.txt, an llms.txt file, and page weight. MaxAEO pairs this readiness checklist with a free AI visibility report, so you see both the technical foundations and the answers they produce.
What the report shows
Sample: slack.com (whole site) · hand-checked 2026-08-31
58 / 100 · sample scoring: pass 1 · improve 0.5 · missing 0
- Missing
Does the site publish Organization / WebSite structured data?
0 application/ld+json scripts and 0 schema.org references in the server-rendered homepage HTML.
Fix: Add Organization and WebSite JSON-LD to the base template so AI engines get name, logo and sameAs links without guessing.
- Missing
Is the FAQ content marked up as FAQPage?
No FAQPage markup anywhere; /features/channels renders a “Frequently Asked Questions” section as plain text.
Fix: Wrap existing FAQ sections in FAQPage structured data — the questions are already written, only the markup is missing.
- Pass
Is the heading structure clean — one H1, ordered sections?
Exactly one <h1> (“All your people and AI agents working together.”); section H2s are present and consistent.
Fix: Keep one H1 per page; phrasing key H2s as buyer questions makes passages easier for AI engines to lift.
- Pass
Can AI bots read the site (robots.txt)?
robots.txt has a single User-agent: * block with 15 path rules — GPTBot, ClaudeBot, PerplexityBot and Google-Extended are all allowed by default.
Fix: Nothing to fix; re-check after any CDN or security change, because bot blocks usually appear there silently.
- Pass
Is there an llms.txt file?
/llms.txt returns 200 as text/plain: a 40 KB hand-written index (“Welcome, humans and bots alike…”) with sectioned links.
Fix: Nothing to fix; keep it in sync when key pages move.
- Improve
Are pages light and fast enough for AI bot fetches?
Homepage HTML alone is 260 KB and took 2.0 s to fetch — inside most AI bots' budget, but with little headroom.
Fix: Trim server HTML and keep time-to-first-byte under one second so bot fetches never time out.
What's in your free report
- Your brand's AI visibility across 8 AI engines — the outcome the six site checks are meant to improve
- Which pages AI engines currently cite for your category, and whether any of them are yours
- An action plan that connects visibility gaps to concrete page and content fixes
- The readiness checklist on this page as a self-audit: structured data, FAQ markup, heading structure, AI bot access, llms.txt and page speed
Compared with other ways to check
| Asking the engine yourself | Traditional SEO tools | AEO Checker | |
|---|---|---|---|
| Coverage | View source and hope you know what to look for | Site audit reports built for Google, not AI engines | The six signals AI engines use, checked against a real site |
| Repeatability | A different checklist every time | Hundreds of issues, no AI prioritization | Same six checks, so progress is visible |
| Competitor context | None | Technical scores, not who AI actually cites | Paired with which competitor pages AI engines cite instead |
| Sources | Blog posts of varying accuracy | Generic best-practice tooltips | A fix for each failed check, tied to how AI engines read pages |
What does an AEO readiness check look for?
Answer engine optimization has a plumbing layer that gates everything above it. Before an AI engine can recommend you, its bots have to fetch your pages within a time budget, parse what the pages are about, and attribute the content to the right entity. A site can publish excellent content and still be invisible simply because a security rule blocks GPTBot, or because nothing on the page tells a model which company it is reading about. The six checks exist because each one maps to a specific step in that pipeline.
They group into four concerns. Machine-readable identity: Organization and WebSite structured data plus FAQ markup tell engines who you are and which text answers which question. Liftable structure: one clear H1 and well-formed section headings let a model extract a passage without dragging in its neighbors. Access and guidance: robots.txt decides whether GPTBot, ClaudeBot and PerplexityBot may read you at all, and llms.txt hands them a curated index. Delivery: page weight and response time decide whether a bot's fetch finishes. The slack.com sample above shows how mixed a strong brand's plumbing can be — perfect bot access and a model llms.txt next to zero structured data.
The practical workflow: run the six checks against your own site using the sample as a template — every check is verifiable with a browser and a robots.txt read. Most fixes are template-level work measured in days. Then measure the outcome, not the checklist: the free visibility report shows whether AI engines actually cite you, which is the number the plumbing exists to move. Re-check quarterly and after any release that touches templates, security or CDN settings.
Who this is for
SEO / GEO leads
Turn 'AEO' from a buzzword into six checks you can run and report on.
Web and content teams
Know which technical fixes matter for AI engines before touching the site.
Agencies
Open a client conversation with a readiness checklist rather than a slide about AI search.
Frequently asked questions
AEO — answer engine optimization, often called GEO — is about being named and cited in AI-generated answers, rather than appearing as a link on a results page. Most SEO foundations still matter, but AI engines add their own requirements: they read pages through their own bots, they lift specific passages rather than whole pages, and they rely on structured data and clear question-and-answer formatting to decide what a page is about.
Because each one maps to a known way AI engines read a site. Structured data and FAQ markup tell them what an entity and a question are; a single clear H1 and question-style H2s make passages liftable; robots.txt decides whether GPTBot, ClaudeBot and PerplexityBot can read you at all; llms.txt is the emerging convention for pointing AI bots at your key pages; and page speed decides whether a fetch completes within the bot's time budget.
It is not required, and no major AI engine has committed to reading it — but it is cheap, harmless and increasingly common among sites competing for AI citations. Think of it as a curated index for AI bots: a short markdown file at /llms.txt that lists your most important pages with one-line descriptions. The check simply reports whether one exists; the fix is a half-hour job.
Blocking an AI bot removes your own pages from what that engine can read when it answers a live question — but it does not remove your brand from the answer, because the engine can still cite third-party pages about you. The practical effect is that competitors and review sites get to describe you. The check lists each major AI bot and whether your robots.txt allows it.
After every site release that touches templates, structured data or robots.txt, and at least quarterly otherwise. Two of the six checks — AI bot access and page speed — drift silently when CDN, security or performance settings change, and both can quietly cut AI engines off from your pages without any visible symptom in Google Search Console.
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