Advisors AI Store Readiness

Advisors AI · Services · Contact · بالعربية

This check does not evaluate visual design. It reads what your page and three public discovery files declare in a form machines parse. You give us one page. We inspect that page plus three public discovery files on the same origin — /robots.txt, /llms.txt, and /sitemap.xml — under a base contract of 10 required signals worth 11 base points. The tool shows what passed and failed, a selected remediation when one is covered, and its acceptance criterion. It does not create or promise a manual report. The ten fixed base weights are 0, 1, 1, 2, 2, 1, 1, 2, 0, and 1; that is why ten signals total eleven points.

Malformed JSON-LD is conditional: only when the checker detects a block that does not parse does it append the failing optional diagnostic jsonld_valid with weight 1. That measured result has 11 rows and 12 possible points. Otherwise the optional row is absent; it is never added as a passing bonus.

Free, with no purchase or account required. No card, no password to your store, no access to your systems. Give the tool one public link and its result appears immediately; no order, manual report, or invoice is created.

An example from our own site

Our About page lacked structured data describing the business and its service, so we added it. Check any page yourself with the tool below and compare.

Each miss carries a concrete remedy

When business or offering data is missing, the remedy includes one JSON-LD template for <head>. It is not a filled block and is not publishable as delivered: its entity type, host-derived name and URLs, SA, product-name placeholder, SAR 0.00, and InStock are defaults or placeholders, not verified business facts. Replace or remove every such field using facts you can substantiate, and validate the resulting JSON before publication. Other misses receive explicit written instructions. The sheet's acceptance criterion is to re-measure: every recorded miss must turn passing. If it does not, the remedy did not close the result, and we say so.

What this sheet does not measure

• It is not a 30-point store or site audit — that is a separate service listed under Services.
• It does not measure whether an AI assistant mentions your business.
• It does not measure AI answer visibility, ranking, or share.
• This check does not predict sales or conversion.

Self-service Readiness Check — public read-only self-check

The result appears immediately in the tool client. It creates no account or service order, does not make its user a service customer, and promises no manual report.

Paid audit order

Create an account, verify your email, and choose the package in My Portal. After a consultation session you receive a formal written scope — what we understood, what we will build, the price and the duration — with an invoice and a payment link. Work begins only after you approve the scope and pay; delivery follows.

Create an account, then choose a package in My Portal.

Or measure it yourself right now

We published the public self-service route of this checker as a tool. Open its connector form in Claude (or configure it in another MCP client), then point it at your own page and read the result. One tool, read-only: it fetches the supplied page and exactly three fixed public discovery files on the same origin. It does not follow links or recursively crawl your site, and it asks for access to nothing.

Open Claude's connector settings, then add a custom connector and paste this endpoint: https://advisorsai.ai/store-readiness-mcp

We do not claim that link opens the add-connector dialog for you — it opens the settings page, and you add the connector from there. You can also find the tool in the official MCP registry as ai.advisorsai/store-readiness, and you do not have to take our word that it is listed: query the registry yourself and read the entry it returns.

Leave the OAuth fields empty; the tool needs no authorization.

A completed result uses one of three explicit states: finding when a measured miss has a selected fix; ready when every weighted readiness signal passes; or no_actionable_finding when measurement completed with misses, but none was both weighted above zero and covered by the checker's fixed remedy list. Selection uses the first eligible miss in that list's fixed order; it is not a discretionary omission.

When a check returns a verified finding, it includes acceptance criteria so you can re-run the check after fixing; if the result is clean, we propose no fix.

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The source reconstruction above documents two specific structured-data changes from the cited Git revision; it is not a stored measurement receipt or a historical whole-page score. Anyone can run a current check and inspect the page-level items in the page source and the remaining discovery items in the public /robots.txt, /llms.txt, and /sitemap.xml. No customer testimonial is shown on this sheet.

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