Schema Checker: Free Schema Markup Checker

Q: How is a schema check done?

A page address is entered; the tool reads the application/ld+json blocks in the page HTML, parses the JSON, recognises every entity's type and lists the required and recommended fields that are missing.

Q: What is the difference between JSON-LD and microdata?

JSON-LD gathers the data in one script block in the head; microdata is spread across HTML tags as itemprop attributes. Google recommends JSON-LD; this tool shows the presence of microdata as information only.

Q: Is FAQ schema still worth it?

Google has narrowed FAQ rich results for most sites; however, FAQPage schema offers directly quotable question-answer pairs to AI answer engines. Marking real questions with short answers is valuable for GEO.

Q: What happens when a required field is missing?

If a required field is missing, Google does not show a rich result for that entity and reports an error in Search Console. If recommended fields are missing, a rich result may still appear with less information; the tool lists the two separately.

Q: How is the schema score calculated?

For every entity, required fields count with weight 2 and recommended fields with weight 1; the page score is the average across entities. A broken JSON block caps the score at 40; without any JSON-LD the score is 0.

Q: Isn't Google's structured data test enough?

Google's rich result test is needed for validation; this tool lists missing fields per type in one place, highlights the types that matter for AI answers and ties the result to the SEO + GEO Readiness Score. Using both gives the best result.

Result

Entities and gaps:

Structured data test

What are structured data and JSON-LD?

The schema checker reads the JSON-LD blocks on a page, recognises every entity's type and lists the required and recommended fields for that type. Missing fields, broken JSON and common mistakes appear in one list. The structured data test is free; a page address is enough.

Structured data labels the information on a page in a form search engines and AI models understand: this is an organisation, this is an article, this is a product and its price. JSON-LD is the format Google recommends; it is added to the page head in a script tag and does not change the visible content.

Two things matter in a JSON-LD check: the block must be valid JSON and the fields the type requires must be filled. A single missing comma voids the whole block; a missing required field stops the rich result from showing.

Example JSON-LD

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Example Co",
  "url": "https://ornek.com/",
  "logo": "https://ornek.com/logo.png",
  "sameAs": ["https://www.linkedin.com/company/ornek"],
  "contactPoint": { "@type": "ContactPoint", "telephone": "+90 850 000 00 00", "contactType": "customer service" }
}

Required: name, url. Recommended: logo, sameAs, contactPoint, address, description.

Schema markup test

Which types are checked?

The tool recognises Organization and LocalBusiness (name, address, phone, opening hours, sameAs), FAQPage (question and answer pairs), Article and BlogPosting (headline, author, dates, image, publisher), Product (name, image, price, currency and availability inside offers), WebSite, WebPage, BreadcrumbList and Person. Types it does not know are listed as "other types".

Field lists

Organization: name, url (required); logo, sameAs, contactPoint, address, description (recommended)
LocalBusiness: name, address, telephone, url (required); openingHoursSpecification, geo, priceRange, image (recommended)
FAQPage: Question objects in mainEntity with name and acceptedAnswer.text filled
Article / BlogPosting: headline, author, datePublished, image (required); dateModified, publisher.logo, mainEntityOfPage (recommended)
Product: name, image, offers.price, offers.priceCurrency, offers.availability (required); brand, sku, aggregateRating, review (recommended)

Rich result test

How it differs from a rich result test

Google's rich result test looks only at the rich result types Google shows and renders the page the way Google sees it. This tool reads every JSON-LD block on the page, counts gaps against the full field lists of the schema.org types and highlights types that matter for AI answers, such as FAQ schema. The two complement each other: close the gaps here first, then confirm with Google's test.

Comparison

This tool compared with Google’s rich result test
	This tool	Google’s test
Scope	All JSON-LD, schema.org field lists	Google’s rich result types
Output	Per-type required/recommended gaps, score	Eligible/not eligible, errors and warnings
GEO	FAQPage, Organization, Article emphasis; link to the Readiness Score	None

Schema and GEO

Why schema matters for AI answers

AI answer engines rely on structured data to understand who a source is and what it says. Organization schema gives the brand, sameAs links the identity, Article schema the author and date, and FAQPage directly quotable question-answer pairs. Complete schema is the subject of five checks in the GEO half of the SEO + GEO Readiness Score.

Check the Schema