Schema Visual Tree
MOD 01 Paste schema and click Analyze
Schema Visualizer &
GEO Readiness Analyzer
Go beyond validation. Visualize JSON-LD, Microdata and RDFa as interactive entity trees and force-directed graphs. Preview Google Knowledge Graph interpretation, simulate AI extraction, score GEO readiness, and predict LLM citation likelihood.
15 Pro Modules
Browser-side Parsing
Privacy Friendly
100% Free
AI Citation Predictor
GEO Scoring
Entity Relationship Graph
MOD 02
Organization/Site
Person
CreativeWork
Product
Other
Drag nodes · Scroll to zoom
Knowledge Graph Preview
MOD 03Entity Schema Timeline
MOD 08 No entities detected yet.
Entity Completeness
MOD 05 Run analysis to check completeness.
GEO Readiness Factors
MOD 06 Run analysis to score GEO readiness.
AI Citation Simulation
MOD 14–15Predicted citation snippet
Run an analysis to generate a predicted AI citation snippet…
AI Search Interpretation
MOD 04Simulated extraction by ChatGPT, Gemini, Perplexity and Claude based on schema clarity, entity signals and semantic coverage.
Run analysis to simulate AI interpretation.
Schema Coverage Heatmap
MOD 09Which schema types are present vs missing on this page. Missing types = unexploited rich-result opportunities.
Run analysis to view coverage.
Rich Result Eligibility
MOD 10 Run analysis to check eligibility.
Entity Overlap Detector
MOD 11 Run analysis to detect issues.
JSON-LD Linter
MOD 12 Run analysis to lint JSON-LD.
Entity ↔ URL Correlation
MOD 13 Run analysis to check URL binding.
Missing Schema Suggestions
MOD 07 Run analysis to see suggestions.
Competitor Schema Comparison
MOD 07Paste two JSON-LD blocks to diff entity types side-by-side and reveal schema gaps.
URL A Entities
Paste two sources above and click Run Comparison.
URL B Entities
How It Compares to Other Tools
MOD 15| Feature | Schema Visualizer | Google Rich Results Test | Schema Markup Validator | Merkle Generator | Ahrefs / SEMrush |
|---|---|---|---|---|---|
| JSON-LD validation | |||||
| Interactive entity tree | |||||
| Force-directed entity graph | |||||
| Knowledge graph preview | |||||
| AI search interpretation (4 engines) | |||||
| GEO readiness score | |||||
| LLM citation predictor | |||||
| JSON-LD linter | |||||
| Competitor schema diff | |||||
| Free, no signup |
Learn: Structured Data, Entities & GEO
What is Structured Data?
Structured data is a standardized way of annotating page content (mostly via Schema.org vocabulary) so machines can read entities, attributes and relationships unambiguously. JSON-LD is the recommended format.
What is Schema Visualization?
Visualization converts dense JSON or microdata into trees and graphs, exposing how an entity (Article, Product, Organization) connects to its attributes and to other entities — making audits and gap-finding 10× faster.
What is Entity Mapping?
Entity mapping identifies real-world things (people, brands, places, products) on a page and the relationships between them. It is how Google's Knowledge Graph and LLMs build a structured understanding of your content.
What is GEO?
Generative Engine Optimization optimizes pages to be surfaced and cited by generative AI engines (ChatGPT, Gemini, Perplexity, Claude). It depends on entity clarity, semantic richness, citable phrasing and clean structured data.
How AI Search Uses Schema
LLM-powered search engines extract entities and facts during retrieval and reranking. Pages with complete Article/Author/Organization schema and unambiguous sameAs links are far more likely to be cited as sources.
Knowledge Graph Explained
A knowledge graph stores entities (nodes) and relationships (edges). Search engines use it to disambiguate queries, populate entity panels, and pass authority between connected entities.