Paste your <script type="application/ld+json"> content here (without the script tags).
Paste JSON-LD to validate
Supports 15+ schema.org types including Article, Product, FAQ, Event, Recipe and more// check json-ld syntax and missing required fields
Validate JSON-LD schema markup instantly. Check syntax errors and find missing required fields for common schema types like Article, Product, FAQ, and more.
Paste your <script type="application/ld+json"> content here (without the script tags).
Paste JSON-LD to validate
Supports 15+ schema.org types including Article, Product, FAQ, Event, Recipe and moreCopy your structured data markup (the content inside <script type="application/ld+json"> tags) and paste it in the input.
Hit the Validate Schema button. The tool checks JSON syntax first, then checks required and recommended fields per schema type.
Review the color-coded results. Red = missing required fields, yellow = missing recommended. Add missing fields and re-validate.
JSON-LD (JavaScript Object Notation for Linked Data) is the recommended format for adding structured data to web pages. Google uses it to understand your content and display rich results in search — like star ratings, FAQ dropdowns, recipe cards, and event listings.
It checks two things: first, whether your JSON-LD is valid JSON (correct syntax, no trailing commas, matching brackets). Second, it checks for missing required and recommended fields based on schema.org specifications for 15+ common schema types.
Required fields (shown in red) are the minimum needed for a schema type to be technically valid according to schema.org. Missing these may cause Google to ignore your markup. Recommended fields (shown in yellow) are strongly suggested by Google for richer search results but are not strictly mandatory.
Yes. If your JSON-LD uses the @graph property to define multiple schemas in one block, the validator will check each schema in the graph separately and report results per schema type.
The validation is performed via a lightweight PHP API on our server, but no data is stored or logged. Your JSON-LD is processed in memory and discarded immediately after validation.
This tool performs a structural and field-presence check against common schema.org rules. Google's Rich Results Test additionally checks value formats, content policies, and eligibility for specific rich result types. Use this tool for quick feedback during development and Google's tool for final verification.
Yes. NewsArticle and BlogPosting share the same required fields as Article (headline, author, datePublished). The validator supports all three types and applies the same rules automatically based on the @type value in your JSON-LD.
Common issues detected include: invalid JSON syntax, missing @context, missing @type, empty field values, missing required fields per type, and missing recommended fields. It won't catch semantic errors like incorrect URL formats or invalid date strings — use Google's tools for those.
Add a <script type="application/ld+json"> block in the <head> or <body> of your HTML with your JSON-LD markup. WordPress users can use plugins like Yoast SEO or Rank Math. This tool validates the JSON-LD content inside those script tags.
A JSON-LD schema validator is a tool that analyzes structured data markup — specifically markup written in the JSON-LD format — to verify that it follows the rules defined by schema.org and recommended by search engines like Google. When you add structured data to your web pages, you're giving search engines explicit signals about your content: what type it is, who authored it, when it was published, what it's about, and more. Getting that markup right is the difference between earning rich results in Google Search and having your structured data silently ignored.
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Google supports three formats for structured data: JSON-LD, Microdata, and RDFa. While all three can technically communicate schema information to search engines, Google strongly recommends JSON-LD for several practical reasons. JSON-LD is embedded in a separate <script> block rather than mixed into your HTML markup, which means it's easier to add, update, and manage independently of your page design. It's also easier to read and write, making it the format of choice for developers and SEO professionals alike.
With JSON-LD, the structured data doesn't need to match visible text on the page, giving you more flexibility when documenting technical attributes that aren't displayed to users. This is especially useful for Product schemas (where you want to document technical specs) or Event schemas (where you need precise ISO 8601 date formats regardless of how dates are displayed visually).
Different schema types have different required and recommended fields. Getting required fields right is essential — missing them often means Google won't process your markup at all. Here's a quick overview of the most common types:
headline, author, and datePublished. Recommended: image, publisher, and dateModified.name, but without offers, aggregateRating, or review, the schema won't qualify for rich results.mainEntity array, where each item is a Question object with an Answer.name and address. Recommended: telephone, openingHours, and geo.itemListElement array with ListItem objects that each have position, name, and item.name, startDate, and location. After Google's 2021 update, events also need eventAttendanceMode and eventStatus for eligibility.name, recipeIngredient, and recipeInstructions. To qualify for recipe rich results, Google also expects image and author.The most frequent issues developers run into with JSON-LD are syntax errors and missing fields. JSON syntax errors — like trailing commas, mismatched brackets, or unquoted property names — are the most disruptive because they prevent the entire JSON block from being parsed. Use the validator to catch these before publishing.
Missing required fields are the second most common problem. A Product schema without an offers property won't qualify for product rich results. An Article schema without an author value won't be associated with a specific byline in Google Discover. These aren't just theoretical SEO improvements — they directly affect whether Google surfaces your content with enhanced visuals in search results.
Empty field values are another subtle issue. Having a property present with an empty string or null value is technically worse than omitting the field entirely in some cases, since it signals that the data is incomplete. This validator flags empty fields as warnings so you can address them proactively.
It's important to understand what a lightweight validator like this one can and cannot do. Schema Validator Lite performs structural validation: it checks that your JSON is syntactically correct and that the expected fields for a given schema type are present. This catches the majority of implementation errors developers make.
What it doesn't check is semantic correctness: whether your date values are valid ISO 8601 strings, whether your URLs actually resolve, whether your image dimensions meet Google's minimums, or whether your content policies comply with Google's structured data guidelines. For that level of validation, Google's own Rich Results Test and Search Console are the authoritative tools.
Think of Schema Validator Lite as your first line of defense during development — fast feedback in your editor before you ever touch Search Console. Use Google's tools for the final review before publishing.
A common pattern in modern SEO is to include multiple schema types on a single page using the @graph property. For example, a blog post might include an Article schema, an Author (Person) schema, and a BreadcrumbList schema all in a single JSON-LD block. This is the recommended approach because it lets schema entities reference each other by ID, creating a richer knowledge graph for search engines to process.
When you validate a @graph structure with this tool, each schema in the graph is checked individually. You'll see a separate result card for each type, with its own missing fields and warnings. This makes it easy to audit complex structured data without losing context.