Structured Data Visualizer: Free JSON-LD Check

The structured data visualizer lets you paste one JSON-LD object and see it as an indented tree, with a quick check for missing required and recommended fields. It is built for SEOs, developers and site owners who want to catch gaps in schema markup before publishing. You get an error and warning count plus a readable view of every property.

What Is Structured Data and JSON-LD?

Structured data is a standardized block of code that describes a page in terms search engines can read, such as an article's headline, a product's name or a business's address. JSON-LD is the format Google's Search Central documentation recommends for it, and it uses the shared Schema.org vocabulary.

A JSON-LD block is a JSON object with three kinds of entries you will see in this tool:

• @context tells search engines which vocabulary you use, normally https://schema.org.
• @type names the kind of thing you describe, such as Article, Product or LocalBusiness.
• Properties like headline, author or offers carry the actual details. They can hold text, numbers, lists or nested objects.

Raw JSON-LD is hard to scan once it has nested authors, offers and addresses. A tree view makes the structure obvious, and a presence check shows which fields you forgot.

How to Use the Structured Data Visualizer

You only need your JSON-LD code, without the surrounding script tag. Follow these steps:

1. Copy a single JSON-LD object from your page source, your CMS or your schema plugin output.
2. Paste it into the JSON-LD Structured Data box. The placeholder shows an Article with a headline, author and publish date.
3. Click Visualize & Validate.
4. Read the banner at the top. It names the detected type, shows a status and gives the number of errors and warnings.
5. Open the Basic Presence Checks list to see each missing field and each field that passed.
6. Scroll to the Structured Data Tree to confirm that nested values such as the author or offers look the way you intended.
7. Fix the markup in your own source, paste it again and re-run until the banner reads clean.

Editing the text after a run clears the old result, so you never read a report that no longer matches your input.

Worked Example: Checking an Article

Say you paste this object: an Article with the headline "Trail Running Tips for Beginners", an author object (a Person named Maya Ortiz) and a datePublished of 2025-03-10, plus the Schema.org context.

The tool detects the type as Article and checks its three required fields: headline, author and datePublished. All three are present, so there are 0 errors. It then checks the recommended fields: description, image and publisher. None exist, so you see 3 warnings and the status "Review notes".

The tree shows the author as a nested block with its own type and name, so you can confirm that the byline is structured and not a plain string. To clear the warnings, add a short description, a main image URL and a publisher organization, then run the check again. If you delete the author instead, the count changes to 1 error and 3 warnings, and the status becomes "Errors Found".

How to Read and Act on the Results

The status banner has three outcomes, and each one tells you what to do next.

Errors

An error means the tool could not find a required field, or the field was empty. A missing context or type is flagged too. Empty text, an empty list and an empty object all count as missing, so a blank offers placeholder will not slip through.

Warnings

Warnings are optional improvements. Add a recommended field only when the information is real and visible on the page. Marking up an image or rating that users cannot see goes against Google's structured data guidelines.

The tree

Use the tree to catch structural mistakes: a price stored as text when you expected a nested offer, a list where you expected one object, or a property placed at the wrong level. Very deep nesting is shown as a collapsed marker after several levels.

Which Schema Types Does It Check?

The tool has a built-in checklist for 12 types. Fields listed as required produce errors, and recommended ones produce warnings.

• Article: requires headline, author and datePublished.
• Product: requires name. Recommended fields are description, image, offers, brand and sku.
• FAQPage: requires mainEntity.
• LocalBusiness: requires name and address. Recommended fields are telephone, openingHours, geo and url.
• Recipe: requires name, recipeIngredient and recipeInstructions.
• Event: requires name, startDate and location.
• Review: requires itemReviewed and reviewRating.
• BreadcrumbList: requires itemListElement.
• VideoObject: requires name, description, thumbnailUrl and uploadDate.
• Person, Organization and WebSite: require a name, and WebSite also needs a url.

If your type is not on this list, the tool still shows the tree and checks the context and type, but it has no field checklist for it.

When Should You Use It?

Use it whenever you want a fast, readable look at one block of markup.

• Before launch: check the JSON-LD your template or plugin generates for a new product, recipe or event page.
• During audits: paste the block from a page you are reviewing and see at once which fields are missing. Pair it with the Website Audit & Performance tools for a wider review.
• Debugging plugin output: confirm whether the author, price or address really ended up inside the markup.
• Teaching and handoff: show a client or developer the exact structure of a schema block without making them read raw code.
• Trust signals: make sure author and organization details are in place, then review the page's wider credibility with the E-E-A-T checker.

Best Practices and Troubleshooting

"Invalid JSON" appears

The tool prints the parser's message, which usually points to the problem. Common causes are a trailing comma, single quotes instead of double quotes, or curly quotes pasted from a document editor. Fix the character and run it again.

You pasted the whole script tag

Paste only the JSON between the opening and closing script tags. The tag itself is not valid JSON and will cause an error.

You pasted an array or a graph

The tool expects one object. If your page uses an array of objects or a graph, paste each object separately and check them one at a time.

The type shows as Unknown

Your block has no type, or the type has no checklist here. Add a valid Schema.org type, or accept that only the tree and basic context check apply.

A field shows as passed but looks wrong

The check only confirms a value exists. Read the tree to confirm a date is a real date, an image is a real URL and a price is a number.

General habits

• Mark up only what users can see on the page.
• Keep values consistent with the visible content, such as the same price, title and author name.
• Use full image URLs that return a working page, and give those images meaningful alt text with the image alt text checker.
• After publishing, confirm the page is crawled and listed by using the Google index checker.

Limitations You Should Know

This tool reads one JSON-LD object and checks that certain top-level fields are present. It does not validate nested objects, so an author with no name inside still counts as an author. It does not read Microdata or RDFa, and it does not check whether a page qualifies for any rich result.

Google decides rich result eligibility, and its requirements differ by feature. For example, Google shows FAQ rich results only for a limited set of sites, so valid FAQPage markup is no guarantee of a display. Treat a clean result here as a good first pass, then test the final page with Google's own Rich Results Test. If you want to see how heavy your markup makes the page, the code to text ratio checker shows how much of the HTML is readable content.

Paste your JSON-LD into the structured data visualizer on this page, run the check and fix every error and warning that applies to your content. A clear tree and a clean banner give you a strong starting point before you publish.