Schema Markup Validator — Check Whether Your JSON-LD Still Does Anything

What this schema validator checks

The tool reads one page and grades the structured data on it. It cannot verify that what the markup claims is true, and it never predicts a rich result or an AI citation — those are decisions made elsewhere.

How the score is calculated

Ten weighted checks. A page with no parseable JSON-LD caps at 10, and any structural failure caps below 50, so a passing number never hides a broken graph. Advisory notes — retired rich-result types, recommended properties — carry no weight.

What structured data actually does — and what it does not

Structured data types that no longer produce rich results

Most advice about schema markup is older than the features it recommends. Two widely deployed types no longer create anything in Google Search — the markup stays valid, and removing it is optional, but expecting a search feature from it is not realistic.

This validator reports both as notes and does not count them against your score. Types that do still produce rich results — Article, Breadcrumb, Product, Review, Event, JobPosting, LocalBusiness, Organization, Recipe, Video and others — are listed in your result when present.

Common schema markup errors and how to fix them

Ordered roughly by how often they turn up on real sites. The first three account for most broken entity graphs.

1. The author is a plain string. author: "Jane Roe" names someone without identifying them — a string cannot carry a URL, a sameAs list or an identifier. Fix: Use a nested Person object with url and sameAs, or an @id reference to a Person entity defined once.
2. A trailing comma breaks the whole block. One invalid character makes the JSON unparseable, and a block that does not parse is ignored in full. Every entity inside it is lost silently. Fix: Validate the block as plain JSON on every deploy. Templating engines add trailing commas when a loop ends early.
3. The same Organization is declared on every page with no @id. Without a shared identifier the same company reads as a new, unrelated object on each URL rather than one entity mentioned many times. Fix: Declare it once with @id such as https://example.com/#organization and reference that @id everywhere else.
4. A mistyped @type. "Blogposting" or "FAQpage" are not schema.org types. Type names are case-sensitive, and a typo voids the entity without any visible error. Fix: Check each @type against schema.org. This validator flags anything it does not recognise.
5. Relative URLs inside the markup. Structured data is consumed away from the page, so "/logo.png" has nothing to resolve against. Fix: Use absolute URLs with scheme and host for url, @id, logo, image and sameAs.
6. Markup that contradicts the visible page. A rating, price or review count in the markup that does not appear on the page is a policy violation, not a shortcut. It risks a manual action. Fix: Only mark up what a visitor can see on the page.
7. Schema injected by a tag manager. Markup added by client-side JavaScript is absent from the server-rendered HTML that many parsers read, so it may never be seen. Fix: Render structured data server-side. If you cannot, verify separately in a tool that executes JavaScript.
8. sameAs pointing at pages you do not control. sameAs is meant to link the entity to profiles that are demonstrably the same entity. Random citations weaken rather than strengthen the signal. Fix: List only official profiles: your own accounts, and authoritative databases where the entry is genuinely yours.

JSON-LD templates you can copy

Five starting points, all structurally valid. Replace the values with your own — never leave placeholder data in production — then re-run the validator above to confirm the block parses and links correctly.

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://example.com/#organization",
  "name": "Example Company",
  "url": "https://example.com/",
  "logo": {
    "@type": "ImageObject",
    "url": "https://example.com/logo.png",
    "caption": "Example Company"
  },
  "description": "One sentence stating what the company does and for whom.",
  "foundingDate": "2019-03-01",
  "sameAs": [
    "https://www.linkedin.com/company/example",
    "https://github.com/example",
    "https://www.crunchbase.com/organization/example"
  ]
}

{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "The article title, under 110 characters",
  "description": "One or two sentences summarising the article.",
  "datePublished": "2026-07-22",
  "dateModified": "2026-07-22",
  "image": "https://example.com/images/article.jpg",
  "author": {
    "@type": "Person",
    "name": "Jane Roe",
    "url": "https://example.com/team/jane-roe/",
    "jobTitle": "Head of Research",
    "sameAs": ["https://www.linkedin.com/in/janeroe"]
  },
  "publisher": { "@id": "https://example.com/#organization" },
  "mainEntityOfPage": "https://example.com/blog/the-article/"
}

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Example Product",
  "image": ["https://example.com/images/product.jpg"],
  "description": "What the product is and who it is for.",
  "sku": "EX-1001",
  "brand": { "@type": "Brand", "name": "Example" },
  "offers": {
    "@type": "Offer",
    "url": "https://example.com/products/example/",
    "price": "149.00",
    "priceCurrency": "USD",
    "availability": "https://schema.org/InStock",
    "priceValidUntil": "2026-12-31"
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.6",
    "reviewCount": "127"
  }
}

{
  "@context": "https://schema.org",
  "@type": "BreadcrumbList",
  "itemListElement": [
    { "@type": "ListItem", "position": 1, "name": "Home", "item": "https://example.com/" },
    { "@type": "ListItem", "position": 2, "name": "Blog", "item": "https://example.com/blog/" },
    { "@type": "ListItem", "position": 3, "name": "This article" }
  ]
}

{
  "@context": "https://schema.org",
  "@type": "LocalBusiness",
  "@id": "https://example.com/#business",
  "name": "Example Studio",
  "url": "https://example.com/",
  "telephone": "+380441234567",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "12 Khreshchatyk St",
    "addressLocality": "Kyiv",
    "postalCode": "01001",
    "addressCountry": "UA"
  },
  "geo": { "@type": "GeoCoordinates", "latitude": 50.4501, "longitude": 30.5234 },
  "openingHoursSpecification": [{
    "@type": "OpeningHoursSpecification",
    "dayOfWeek": ["Monday","Tuesday","Wednesday","Thursday","Friday"],
    "opens": "09:00", "closes": "18:00"
  }],
  "sameAs": ["https://www.facebook.com/example", "https://www.instagram.com/example"]
}

Does valid schema guarantee rich results or AI citations?

Schema markup validator — FAQ