Synthetic Answer Extraction Simulator
The DirJournal Synthetic Answer Extraction Simulator is a GEO utility that tests whether an AI model can parse and retrieve specific facts from a given webpage structure.
Limited to 5 simulations per minute. The page is fetched server-side and the first ~12,000 characters are passed to Claude haiku 4.5 — same first-pass surface a generative engine sees.
Test Your Page for Generative AI
Proper heading hierarchies and data tables dictate whether an AI can confidently extract your answer — a fact buried three paragraphs into a wall of prose extracts far less reliably than the same fact placed under a question-shaped H2.
This simulator exposes that gap directly. If the model returns FailedToFind on a page that actually contains the answer, the structure — not the content — is what needs work.
How to Run the Simulation
- 1Enter the URL you want to test. The page is fetched server-side, so it sees the same pre-hydration HTML Googlebot and AI crawlers see first.
- 2Type a specific question an end-user might ask. The more concrete the question, the more useful the signal — "What does this company do?" is harder to evaluate than "What year was the company founded?"
- 3Review the AI's answer to identify missing structure or context. Success with a clean cited excerpt means the page is AEO-ready for that query. Hallucination or FailedToFind points to where structure needs to be added.
Frequently Asked Questions
What is an AEO extraction tester?
An AEO extraction tester is a sandbox that mimics the read pass a generative search engine performs on a single page before composing an answer. You supply a URL and a target query; the tool fetches the page, strips chrome, hands the text plus the query to a constrained LLM, and reports whether the model could find a verbatim answer, found nothing, or could only answer by inferring beyond the text.
Why did the AI fail to find the answer on my page?
Three common causes: the fact is rendered by client-side JavaScript and missing from the initial HTML; the fact is present but buried under heavy chrome (navigation, ads, comment widgets) the extractor couldn't strip; or the fact is implied across multiple paragraphs without being stated in one place. The fix in all three cases is structural — put the fact in a single sentence, in the server-rendered HTML, near a heading that names it.