Free AI Retrieval & AIO Readiness Checker
An AI model reads your page and rates how ready it is to be found, understood and quoted: structure, answer clarity, factual density and machine-readability. You get a readiness score, pass/fail checks and concrete fixes. It is the model’s judgement of your page — no answer engine is queried, and the score can shift between runs.
- ✓ Direct answers — key questions answered in the first sentence
- ✓ Semantic structure — headings and sections that say what each part is about
- ✓ Citable & authoritative signals — a named author with a linked bio
- ✓ Machine-readable main content — clean, parseable text
- ✗ Factual density — few concrete figures or dates a model could quote
- ✗ Entity clarity — the page never names its subject in plain terms
- Add concrete facts — stats, dates, named sources — so AI has citable claims.
- Name the page’s subject in plain terms up front to sharpen entity signals.
AI retrieval optimization (AIO / LLM SEO)
AI assistants don’t read a page the way a classic crawler does — they retrieve passages and synthesize an answer from them, citing sources. To be quoted, a page needs clear structure, direct answers, factual specificity, and machine-readable signals. This is the emerging discipline behind the acronyms AEO, GEO, AIO and LLMO — optimizing to be useful to AI.
What this checks
- Semantic structure — headings and sections that tell a model what each part of the page is about.
- Direct answers & factual density — concrete, citable statements over fluff.
- Entity clarity & authority signals — who/what the page is about, credibly.
- Machine-readability — clean main content an LLM can parse.
For a full site-wide view, run the complete audit — it scores AEO, GEO, and AIO across every page.
Frequently asked questions
What does the AI retrieval readiness score actually measure?
An AI model reads your live page and rates it on structure, answer clarity, factual density and machine-readability, then returns one readiness score with pass or fail checks. It is the model’s judgement of your page, not a measurement of any engine’s behaviour, and because the model chooses how to weigh things the score can move a little between runs. Treat large gaps as real signals and small differences as noise.
How is this different from a normal SEO or ranking check?
Traditional SEO checks focus on what helps a page rank in the classic blue-link results, such as title tags and keywords. This one looks at whether a passage could be lifted from your page and quoted on its own. A page can rank well and still bury every answer three paragraphs deep, which is what these checks surface.
Will improving my AI retrieval score make AI tools cite my page?
Nobody can promise that, and we won’t. Engines decide what to cite on relevance, authority, freshness and their own indexing, none of which this or any tool controls, and no free service can even tell you from the outside whether you were cited — your own Search Console Generative AI report and Bing Webmaster Tools AI Performance can. What a higher score does is remove structural and clarity barriers on your side, which is the part you control.
How should I act on the checks and recommendations?
Start with any failed checks, since those flag the clearest barriers to retrieval, such as missing headings, vague answers, or thin factual content. Then work through the numbered recommendations, which each explain why the change helps. Re-run the checker after editing the page to confirm the readiness score has improved.
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