JSON-LD: readable by machines, tolerated by developers, debugged by SEOs at hours nobody should be working.
Paste your JSON-LD or fetch structured data from any URL. See it as an interactive tree with type badges, property counts, and nesting depth — so you can spot what's there, what's missing, and what's nested three levels deeper than it should be. No logins. No "upgrade to see results." Just the tree.
Extracts all <script type="application/ld+json"> blocks from the page.
Some sites may block cross-origin requests.
Paste or fetch schema to see the tree.
{ "@type": "Product", ... }
Background
What a structured data visualizer actually does
Structured data — the JSON-LD sitting inside your page's <script type="application/ld+json"> tag — is not meant for humans. It's a nested block of objects, arrays, and key-value pairs written for search engines. You're not supposed to read it. You read it anyway, because something broke and the validator is being unhelpful.
A schema markup visualizer takes that JSON-LD and turns it into a tree. Every @type gets a colour-coded badge. Every property is indented under its parent. Every nesting level is visible at a glance. Instead of counting braces and matching brackets, you see the structure the way Google sees it — hierarchical, typed, and explicit. The thing you were doing manually, except now you can stop.
Paste your JSON-LD or enter a URL, and the tool builds an interactive tree with expand/collapse controls, a type and property inventory, and the nesting depth of your schema. It also auto-repairs common JSON issues — trailing commas, single quotes, stray comments — so malformed markup still renders instead of throwing an error and leaving you to figure out which of your 47 closing braces is the wrong one.
Use cases
When to use this tool
A few situations where staring at raw JSON-LD wastes time and a visual tree saves it. You've probably been in at least three of these this month.
Debugging
An Offer sitting outside its parent Product. AggregateRating floating at root level instead of inside anything useful. These mistakes are invisible in raw JSON but obvious in a tree. You see exactly where each type ended up — and whether that's where it belongs.
Auditing
The summary panel counts every @type and property in your markup. Three types or twelve. Whether your Offers have priceValidUntil. Whether brand is a typed Organization or just a string someone pasted in. The inventory you'd build manually, already done.
Competitor analysis
Enter a competitor URL. The tool fetches their JSON-LD and builds the same tree. See which types they use, what properties they include, and how deeply they nest — without right-clicking "View Source" and scrolling past 400 lines of GTM.
Learning
If you're new to structured data, the tree view makes the parent-child relationships click. Load the sample schema, expand each node, and see how Product contains Offer, how Offer contains priceSpecification. schema.org's documentation explains this. Sort of.
Pre-flight check
Before running Google's Rich Results Test, use the tree to confirm your schema looks right structurally. Catch the missing required property, the duplicate type, the orphaned object — before Google catches it for you in a less friendly way.
Migration
Switching CMS, changing theme, or refactoring schema templates? Visualize the old and new markup side by side — or use the Schema Comparison tool for a proper diff. Either way, you'll know if something got lost in the move before Google tells you.
How it works
How the visualizer reads your schema
Two input methods. Paste mode takes whatever you give it — the contents of a <script type="application/ld+json"> tag, a raw JSON object, or even slightly broken JSON with trailing commas and single quotes. The tool parses it as-is first. If that fails, it runs a repair pipeline: stripping trailing commas, swapping single quotes for doubles, wrapping fragments in arrays, removing JavaScript-style comments. If the repair works, you get a warning banner and a tree. If it doesn't, you get a clear error. Not a blank screen. Not silence.
URL mode fetches the page through a CORS proxy, finds all JSON-LD script blocks in the HTML, and parses each one. If the page has multiple schema blocks — a Product, a BreadcrumbList, an Organization — you'll see all of them in one tree. No need to view-source and manually find the right <script> tag buried between analytics snippets.
ℹ️
The summary panel
The Overview tab gives you total types, total properties, maximum nesting depth, and whether there are arrays. The Types tab lists every @type with instance counts. The Properties tab lists every unique property key across all types. Think of it as the inventory you'd normally build in a spreadsheet — except it's already done.
Inspection guide
What to look for in the tree
A well-structured schema tree tells a clear story. When it doesn't, these are the things that give it away.
Nesting hierarchy. Product types should contain their Offers, not sit beside them. AggregateRating belongs inside Product, not floating at root level like it owns the place. If a type badge appears at the wrong depth, the schema won't produce the rich result you expect. The tree makes this obvious. The raw JSON does not.
Required properties. Google's documentation lists required and recommended properties for each type. The Properties tab in the summary gives you a quick inventory. If you're targeting Merchant Listings and you don't see availability, price, and priceCurrency under Offer — that's your gap. Better to find it here than in a disapproval email from Merchant Center.
Type correctness. The tree badges each @type with a colour. Product, Offer, Organization, BreadcrumbList, AggregateRating — each gets its own tag. If you see a type you don't recognise, or one that shouldn't be there, you've found something worth investigating. CMS templates are creative like that.
Depth and complexity. Some schemas nest 6 or 7 levels deep. Others are flat. Neither is inherently wrong, but if your ProductGroup → hasVariant → Product → offers → Offer chain goes deeper than you expected, the tree makes it visible. You can decide whether that's intentional or whether your template is generating wrapper objects nobody asked for.
Common questions
Frequently asked questions
What is a schema markup visualizer?
A tool that takes structured data — typically JSON-LD — and renders it as a visual tree. Instead of reading raw code and counting braces, you see each schema type, property, and value in a hierarchical view with expand/collapse controls. Types are nested inside their parents. Properties are listed under each type. The structure that Google sees, made visible to you.
How is this different from Google's Rich Results Test?
Different job. Google's Rich Results Test checks whether your page qualifies for specific rich results — Product Snippets, FAQ panels, that sort of thing. This visualizer shows you the full structure of your JSON-LD as a tree, regardless of which rich result you're targeting. Use this tool to understand and debug your schema structure. Use Google's tool to confirm you'll actually get the rich result. Two steps, two tools.
Can I visualize structured data from any website?
Yes. Enter any URL in the Fetch tab and the tool extracts all JSON-LD blocks from that page. Some sites block cross-origin requests — in which case, view the page source, copy the JSON-LD, and paste it in the Paste tab. Slightly more effort. Same result.
What types of structured data does this support?
All of them. Product, Organization, LocalBusiness, Article, FAQPage, BreadcrumbList, HowTo, Event, Recipe — the visualizer reads the JSON structure and renders whatever it finds. Any valid schema.org type works. If Google supports it, the tree will show it.
What happens if my JSON-LD has errors?
The tool tries to fix it before giving up. It handles trailing commas, single quotes instead of double quotes, JavaScript-style comments, and unwrapped fragments. If the repair works, you get a warning banner explaining what was fixed and the tree still renders. If it's too broken, you get an error pointing to the parse failure. Not a blank screen.
Does the visualizer validate my schema against Google's requirements?
No. This tool shows you structure — what's in your JSON-LD and how it's nested. It does not check whether your markup meets Google's specific requirements for rich results. For that, use this tool first to understand what you have, then run it through Google's Rich Results Test. Structure first, eligibility second.
Can I compare two schemas side by side?
Not here — but we built a separate tool for that. Schema Comparison lets you paste two schemas and see a side-by-side diff. Two modes: Before/After for tracking changes to your own markup, and Structural for comparing against competitors at the type and property level. The tool this tool needed a friend for.
What does nesting depth tell me?
How many levels deep your schema goes. A flat schema (depth 2–3) is typical for simple pages. E-commerce pages with ProductGroup → hasVariant → Product → offers → Offer → priceSpecification can go 5–7 levels deep. Excessive depth isn't necessarily wrong, but it can mean your CMS template is generating wrapper objects nobody asked for. The tree makes it visible. Then you can decide.
More structured data tools
Visualize, compare, generate. The schema markup workflow, without the tab-switching.