How do I optimize this
page for AI search?
Point Moose at a URL and he reads it the way a crawler does. He checks whether an engine can reach the page, whether it can lift an answer out of it, and whether it has a reason to trust it. The copy comes last, and the findings come back in that order.
I can audit that page. Confirm the source below and add the query you want it to win, if you have one in mind. If you leave it blank I will infer one from the page and audit against that.
GPTBot is training only, so blocking it does nothing to your ChatGPT search visibility. Claude-SearchBot is retrieval, and blocking that one removes the page from Claude answers entirely.
Fix the two retrieval findings first. Then this, which is the highest-value content change on the page.
Query intent reads as commercial-informational, so a dictionary opening is not required. A one-paragraph direct answer is. There is no definition, summary or step list in the first 15% of the page.
Payroll has never been more complicated. Between remote work, new state filing rules and a compliance landscape that shifts every quarter, growing teams are under more pressure than ever to get it right.
Multi-state payroll compliance means registering as an employer in every state where an employee lives, withholding that state's income tax, and paying its unemployment insurance. If your team works across state lines, you owe filings in each of those states, not only the one your office sits in.
Chief desk supervisor. Meridian Payroll is invented for this page. The findings, the wording of them, and the order they arrive in are all real.
Four jobs, in a fixed order
Nothing in tiers two to four does anything if tier one fails. The audit checks them in this order, and the recommendations come back in this order.
Can an engine fetch this page, read it without running JavaScript, and follow the links out of it? These are pass or fail, and a failure here means nothing else on this list can help you.
Without these an engine cannot cite the page at all, so these findings are stated as fact.
An engine needs one passage it can lift out and stand behind without the rest of the page. One claim per paragraph, no orphan pronouns, one name per thing, and the answer somewhere near the top.
Supported by large observational studies of citation behaviour, and not tested on your specific page.
Whether a reader, or an engine, can tell when this was written. Real dates in schema and visible on the page, and how recent they are.
Moose will not tell you to add a date it already found on the page.
Heading wording, paragraph rhythm, coverage of the adjacent question, and the sourcing of your claims. Worth doing and cheap to do, after tier one is fixed.
Low cost and sensible. There is no evidence it increases AI citations on its own, and the audit says so.
Eight weighted categories, and what each one looks at
The score is one number over eight categories. Every one of them is something you can go and look at on the page yourself.
Real date signals, both in schema and visible on the page, and how old they are. A page with no date at all is a page an engine has to guess about.
Coverage breadth and heading outline depth against the query. Never a word count, because there is no minimum word count for AI visibility.
Whether the claims on the page are attributed and sourced. Named sources, links out to them, and evidence a reader could follow.
Headings, title, paragraph shape. The scaffolding that tells an engine which part of the page is the answer to which question.
How readable the meaning is without the surrounding context. Repeated named entities, consistent terminology, plain sentence construction.
How easily a self-contained chunk can be pulled out. Lists, tables, short definitional passages, sections that finish their own thought.
Whether there is anything here worth pointing at: original figures, named sources, specific claims rather than restated consensus.
Four sub-checks on whether a single passage answers the question when read alone.
Answer readiness: four checks on whether a passage stands alone
Answer engines work with passages pulled out of a page. These four checks ask whether any passage on your page makes sense when read alone, and each one hands back the paragraph that failed.
Flags paragraphs carrying too many claims at once. Four or more sentences, or two-plus sentences stacked with three or more conjunctions or four or more commas. An engine cannot lift a clean answer out of a paragraph that is doing five jobs.
Reciprocity agreements between states can reduce the number of returns you file, and while they are common in the Midwest, they do not cover unemployment insurance, which each state administers separately, and they do not apply to local taxes in cities like Philadelphia, so one remote employee may still create three filing obligations.
Flags paragraphs that lean so hard on pronouns that the subject disappears when the paragraph is read on its own.
It applies to them as soon as they cross the threshold, and once that happens they have to register with it before the next quarter closes.
Catches a page flip-flopping between a full name and its acronym, and catches topic drift where the dominant entity changes from paragraph to paragraph.
State Unemployment Insurance in the opening section, SUI from the third heading onward, SUTA in the FAQ. Dominant entity also changes at paragraph nine, from payroll tax to worker classification.
Checks whether the first 15% of the page contains a definition pattern, a summary or TLDR, or a short step list, and how many words a reader wades through before hitting it. Query intent is read first, so a commercial page is not punished for skipping a dictionary opening.
Intent read as commercial-informational. The first definition pattern appears 640 words in, after two customer stories. Nothing in the opening 15% answers the query.
Each recommendation says how strong the evidence is
Nobody knows exactly how answer engines pick a citation. Each item carries a tier, and the tier sets how firmly it is worded.
A retrieval precondition. Without this, AI engines cannot cite the page at all. Stated as fact, because it is testable and it either passes or it does not.
Supported by large-scale studies of AI citation behaviour. Recommended with confidence, but framed as strengthening quotability rather than guaranteeing a citation.
Low cost and sensible, with no evidence it increases AI citations on its own. Offered last and labelled, so you can skip it.
It uses what you already know about the page
Moose reads your Search Console numbers for the URL and your own AI visibility history for it, then adjusts the recommendations. If the page already ranks, the changes stay additive. If nobody has found it yet, bigger changes are on the table.
Connect it once, on any paid plan, and every recommendation arrives with a risk level attached.
Moose protects what is working. Support blocks and clearer answer extraction come first, ahead of touching the title, the H1 or the core framing.
Bigger swings are on the table, including coverage for the adjacent queries the page nearly answers already.
Moose already tracks which of your URLs get cited. He looks back 90 days on this one before he suggests anything.
Common questions
Does schema markup help me get cited by AI?
The best available evidence says no, and Moose will never recommend schema.org or JSON-LD as a way to improve AI visibility. Answer engines read visible page text. Schema still has uses in classic search, so this is not advice to remove it. It is a statement that adding it is not an AEO lever. A visible question and answer section on the page is fine to recommend, because a reader can see it.
What about llms.txt or an AI sitemap?
Same answer. Machine-readable files aimed at answer engines have no evidence behind them for citations, so Moose does not recommend them.
How much does an audit cost me?
On the free tier, nothing beyond your own electricity. It runs on a local Gemma 4 model on your machine, and there is no monthly cap. It does need a local model downloaded and loaded first, and if there is not one it tells you that instead of guessing at an answer.
Will fixing these things get me cited?
No one can promise that. The retrieval preconditions are different: if a retrieval crawler is blocked or the page has no server-rendered text, engines cannot cite you, and fixing that is stated as fact. Everything after that is framed as strengthening quotability and reader trust, because the direct effect on citations is not something anyone can currently prove.
My page is a JavaScript app. Is that fatal?
It is the finding that outranks almost everything else. No major AI crawler except Googlebot executes JavaScript, so if your readable text only exists after rendering, most engines see an empty page. The audit reports the actual numbers: static characters, rendered characters, and static coverage as a percentage.
Do I have to apply the changes myself?
You can. Every recommendation gives you the current text and the replacement copy, so it is a copy and paste. If WordPress is connected you can stage the approved changes and publish them from the audit, and nothing goes live without you approving it.
More things to ask Moose
All use casesOne question, five real engines, and the sentence you appear in. Free on every plan.
When the page does not exist yet. The current results, People Also Ask, and the sources behind the brief.
Before you audit a page, find out whether you already have three of them competing.
The context that decides whether a page gets protected or rewritten.
A workflow finds the page that should be answering the topic, audits it, and stages the fix.
The full list, and what Moose does step by step in each one.
Start with the page you
most want cited.
Paste the URL into a chat. You get the crawler check, the content gap, link health, answer readiness, and copy you can publish, in the order it has to be done.