Structured Data & Schema Checker
Validate Schema.org JSON-LD and microdata markup, @context integrity, required properties, and Rich Result eligibility for search engines and AI crawlers.
Structured Data Health: 100/100 (3 Entities)
Detected 1 JSON-LD script tag(s) containing 3 entity definition(s). No microdata. Syntax valid.
Standard Entity Validation Matrix
Audit of core Schema.org entities required for high-visibility Google Rich Snippets and AI entity grounding.
| Schema Type | Status | Diagnostic Details |
|---|---|---|
| Organization | PASS | Valid (AIROO) |
| WebSite | PASS | Valid (AIROO Diagnostics Platform) |
| BreadcrumbList | PASS | Valid schema structure |
| Product | NOT FOUND | Not detected on page |
| FAQPage | NOT FOUND | Not detected on page |
| SoftwareApplication | NOT FOUND | Not detected on page |
| Article | NOT FOUND | Not detected on page |
Detected Entity Explorer (3)
Name/Headline: “AIROO”
https://schema.orgView Raw JSON-LD Snippet
{
"@type": "Organization",
"name": "AIROO",
"url": "https://airoo.org",
"logo": "https://airoo.org/logo.png",
"sameAs": [
"https://twitter.com/airoo_org",
"https://github.com/watttorideau/airoo"
]
}Name/Headline: “AIROO Diagnostics Platform”
https://schema.orgView Raw JSON-LD Snippet
{
"@type": "WebSite",
"name": "AIROO Diagnostics Platform",
"url": "https://airoo.org",
"potentialAction": {
"@type": "SearchAction",
"target": "https://airoo.org/tools?q={search_term_string}",
"query-input": "required name=search_term_string"
}
}https://schema.orgView Raw JSON-LD Snippet
{
"@type": "BreadcrumbList",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"name": "Home",
"item": "https://airoo.org"
},
{
"@type": "ListItem",
"position": 2,
"name": "Tools",
"item": "https://airoo.org/tools"
}
]
}Evaluation Dimensions
Weighted assessment across key technical and business factors
All 1 JSON-LD block(s) parsed cleanly.
3 entities checked for schema.org @context compliance.
3 valid, 0 warning(s), 0 invalid.
3 of 7 core entity types discovered.
Diagnostic Findings
Automated architectural, economic, and technical observations
No Findings in this Category
The input parameters do not trigger high architectural or economic risk flags.
Structured Data & Entity Graph Best Practices
Strengthen search engine understanding and AI crawler citations with rich schema graph integration.
Immediate Execution Milestones
- Deploy an Organization schema with verified official logo, sameAs social links, and contact points.
- Implement BreadcrumbList on all interior pages to enhance search snippet navigation and hierarchy.
- Use @graph arrays to logically interconnect entities (e.g. WebSite -> Publisher -> Organization) in a unified JSON-LD script.
- Test any newly deployed schemas with Google Rich Results Test to confirm rich snippet eligibility.
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Robonom architects schema graphs, AI search entity indexing, and automated structured data pipelines for enterprise platforms.
How It Works
Extract Markup
Parses all <script type="application/ld+json"> script tags and inline Microdata attributes.
Validate Schema Syntax
Validates JSON format, Schema.org @context integrity, and nested @graph entity relationships.
Property Completeness Audit
Audits mandatory and recommended fields for Organization, WebSite, Breadcrumbs, Product, and Articles.
Rich Result Readiness
Provides remediation recommendations to maximize Google rich snippet display and AI search citation.
Frequently Asked Questions
Why is JSON-LD preferred over Microdata?
Google and major search engines strongly favor JSON-LD because it lives cleanly inside <script> tags in the page head, decoupleable from HTML template layout and less prone to breaking during frontend redesigns.
Does passing this audit guarantee Google Rich Results?
Passing schema validation is a mandatory prerequisite for Google Rich Snippets, but actual display in SERPs also depends on overall site authority, search intent, and Google algorithm policies.
How do AI search engines (SearchGPT, Perplexity) use structured data?
AI search crawlers parse Schema.org entity graphs to build verifiable knowledge representations of your organization, products, authors, and citations without hallucinating details.
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