See what your structured data actually tells search engines.
Inspect, validate, understand and improve structured data without guessing what your markup is doing.
Inspect JSON-LD, Microdata, and RDFa in their original context. Validate syntax, Schema.org vocabulary, and Google documented requirements separately. Trace entity relationships without fabricated claims or magic scores.
- Server-rendered markup only · no site-wide crawl
- Pinned Schema.org vocabulary releases (v15.0+)
- Versioned Google Search feature requirements catalog (v2.4)
- Zero invented facts or fake ranking score estimates
TECHNOLOGY & BUSINESS ECOSYSTEM
Built Around Modern Technology
Platforms and tools across our technology ecosystem. Logos identify technologies, not client relationships or endorsements.
Technical Methodology & Transparency
Built on verifiable engineering standards, not heuristic guesses
Schema.org Pinned Releases
Evaluated against pinned vocabulary definitions (v15.0+), not unversioned heuristics.
Google Documented Requirements
Separately checks Google's published search feature rules (v2.4 catalog).
Multi-Syntax Extraction
Inspects JSON-LD script blocks, Microdata scopes, and RDFa attributes in their original DOM context.
Entity Graph & Identity
Traces @id connections, relationship hierarchy, and flags orphaned or duplicate entities.
Evidence-Based Diagnostics
Every finding maps strictly to OBSERVED, INFERRED, NOT_DETECTED, or UNAVAILABLE states.
Zero Invented Business Facts
Grounded improvement proposals only use verified page facts and explicit inputs.
Core Architecture
What the Schema Analyzer actually does
Structured data inspection separated into four distinct, observable stages. No magic scores, no bundled assumptions.
Inspect
See every structured-data block and how it was interpreted across JSON-LD, Microdata, and RDFa without flattening the DOM.
Validate
Check syntax, Schema.org vocabulary, documented Google requirements, and page consistency as distinct, unbundled checks.
Understand
See how Organization, WebSite, WebPage, Person, and Product entities connect through explicit @id references and parent hierarchy.
Improve
Generate grounded suggestions and corrected JSON-LD using observed values rather than inventing business facts.
Inspection Pipeline
Deterministic End-to-End Workflow
How the analyzer processes your page. Every step is bounded, verifiable, and rule-stamped.
Fetch server-rendered HTML
Safe, SSRF-protected single-URL fetch inspects the exact server-rendered markup delivered to search engine crawlers.
Extract structured data
Isolates JSON-LD script tags, Microdata scopes (itemscope/itemprop), and RDFa attributes while preserving original DOM locations.
Normalize & path-annotate
Converts blocks into bounded, standardized trees with RFC 6901 JSONPath coordinates (e.g., $.@graph[0].publisher).
Multi-layer validation
Evaluates syntax, Schema.org vocabulary definitions, Google documented feature requirements, and on-page content alignment.
Build entity relationships
Resolves conservative @id identities, builds relationship edges (publisher, isPartOf, author), and surfaces potential duplicates.
Explain & generate fixes
Translates technical findings into plain-language guidance and creates corrected, copyable JSON-LD without fabricated data.
Architectural Principles
Why the Schema Analyzer result is different
Engineering precision instead of generic SEO scoring. How our analysis models structured data truthfully.
Evidence before explanation
The system first determines what was actually observed in the document before attempting any explanation. Every observation belongs to an explicit evidence class (OBSERVED, INFERRED, NOT_DETECTED, UNAVAILABLE). Nothing is assumed.
Validation layers stay separate
A schema block can be 100% valid Schema.org vocabulary while missing Google's required properties for an Article snippet. Conversely, markup can meet Google's minimum requirements while containing invalid properties. We never mix these into a single confusing status.
Identity is conservative
Entities are never merged merely because their names look similar. Two Organization blocks remain distinct nodes unless linked by an exact matching @id or explicit relationship edge. This prevents accidental identity poisoning.
AI does not invent business facts
When suggesting fixes, our AI operates within strict prompt fences. If your page does not publish a telephone number, return policy, or price, the tool flags it as an omission rather than inventing placeholder values that violate search policies.
No magic composite score
Structured data is a precise machine-readable contract. Compressing syntax errors, vocabulary nuances, and feature eligibility into an arbitrary 'SEO score' obscures real engineering defects. We provide exact itemized diagnostic counts instead.
Multi-Layer Verification
Four independent validation layers
Because a valid Schema.org vocabulary term does not guarantee Google feature eligibility, each layer reports findings separately.
Syntax & Extraction
Structural integrity and JSON compliance
- JSON-LD syntax validity, trailing commas, unescaped quotes, and brace balance
- Duplicate key detection within single JSON objects (which causes silent parser overrides)
- Multi-type array syntax and @context URI validation
- Microdata itemscope/itemprop nesting and RDFa prefix resolution
Schema.org Vocabulary
Conformance with official specifications
- Type existence checked against pinned Schema.org release (v15.0+)
- Property legitimacy against declared @type domain definitions
- Value shape validation (Text, URL, DateTime, Boolean, Number, nested Thing)
- Identification of deprecated terms or unofficial custom properties
Google Documented Requirements
Published Search feature rules catalog
- Checks against ShubhDigi's versioned catalog of Google's published documentation (v2.4)
- Categorization into Mandatory Required properties vs Recommended properties
- Supported feature types: Article, Product, Organization, BreadcrumbList, LocalBusiness, FAQPage
- Clear disclaimer that meeting requirements does not guarantee rich result display
Page Content Consistency
Alignment between markup and visible HTML
- Headline check: Schema headline property vs visible H1 heading
- Author check: Schema author name vs visible page byline text
- Canonical URL alignment: Schema url or mainEntityOfPage vs HTML canonical link
- Evaluated only on URL analysis; isolated JSON-LD paste cleanly records 'Not Evaluated'
Entity Graph & Disambiguation
See how search engines connect your entities
Modern search engines parse structured data as an interconnected entity graph. Isolated script blocks that omit @id references force crawlers to guess whether two objects represent the same company or disconnected entities.
Explicit @id Identity Resolution
Entities with canonical URIs resolve into unified nodes. A WebSite correctly references the parent Organization node instead of declaring a duplicate entity.
Structural Anonymous Nodes
Nested properties without declared IDs stay scoped to their parent container. We never invent synthetic identities or guess connections.
Duplicate Entity Candidate Detection
When multiple script blocks declare conflicting Organization or WebSite definitions, the analyzer flags them for review before search engines become confused.
Intended Audience
Who needs a developer-grade Schema Analyzer?
Built for practitioners who require deterministic evidence over marketing hand-waving.
Technical SEO Teams
Audit staging and production pages before search engines crawl them. Confirm that newly deployed JSON-LD adheres to Google feature guidelines without relying on external search consoles.
Front-End Developers
Trace syntax breakages down to exact block IDs, JSONPath coordinates, and source line numbers. Debug complex nested @graph arrays without guessing which script tag caused the failure.
Agencies & Consultants
Deliver rigorous, transparent structured data audits. Show clients exact entity graphs, missing Google required properties, and rule version stamps that build authority and trust.
Ecommerce Teams
Verify intricate Product, Offer, AggregateOffer, MerchantReturnPolicy, and Brand relationships. Ensure price, currency, and availability fields match across nested entities.
Content & Publishing Teams
Check Article, NewsArticle, and BlogPosting schemas. Validate that author names match visible bylines and publisher nodes link correctly to the parent Organization entity.
Website Owners & Founders
Understand what search engines extract from your website in plain language. Use the built-in generator to produce valid Organization and LocalBusiness markup with zero fabricated facts.
Real-World Edge Cases
Structured data problems caught before search engines see them
Silent defects that traditional validators frequently overlook or lump into generic errors.
Syntax Breakage & Broken JSON-LD
A single unescaped quote, trailing comma, or misplaced bracket causes browser JSON parsers to abort, discarding every entity inside the block without warning.
Duplicate & Orphaned Entities
Plugins frequently inject competing Organization or WebSite schemas with differing names and no matching @id, leaving search engines unable to determine canonical brand identity.
Contradictory Page Content
Schema declaring prices, headlines, or author credentials that do not match the visible text on the page violates Google's fundamental structured data quality guidelines.
Phantom & Deprecated Properties
Using non-standard properties that sound intuitive but are not defined in Schema.org, or relying on deprecated attributes retired from search engine documentation.
Missing Google Required Properties
Markup may be technically valid Schema.org yet miss mandatory properties required by Google for rich feature rendering (e.g., missing author or image in Article).
Real Schema Scenarios
Supported Schema.org types & inspection scenarios
What each entity represents in machine-readable markup, what our analyzer observes, and what practitioners must verify.
Legal business identity, corporate brand, or institution
name, url, logo, sameAs social links, contactPoint
The website collection published by an Organization
name, url, publisher reference, potentialAction (SearchAction)
The specific web document currently being inspected
url, name, isPartOf website link, about / primary entity link
News, editorial, or knowledge base article content
headline, datePublished, dateModified, author, publisher, image
Physical or digital goods offered for sale
name, image, description, sku, offers (Offer / AggregateOffer)
Physical storefront or localized service business
name, address (PostalAddress), geo (GeoCoordinates), telephone
Author, founder, contributor, or executive individual
name, url, sameAs profiles, jobTitle, worksFor link
Navigational trail showing page position in site hierarchy
itemListElement array with position, name, and item URI
E-E-A-T & Trust Standards
Methodology & Technical Disclosures
Engineering credibility through transparent rules, explicit limitations, and strict determinism.
Versioned Rule Catalogs
Every report explicitly stamps the rule versions that generated its findings:
- Schema.org Vocabulary: Pinned Release v15.0+
- Google Eligibility Catalog: Documented Rules v2.4
- Consistency Catalog: Conservative Text Heuristics v1.2
If rules change in the future, previous reports remain frozen as historical records with clear re-analysis notices.
Strict AI Fencing & Validation
Artificial intelligence is never permitted to guess or hallucinate corporate facts:
- Zero Invented Facts: Telephones, prices, or ratings are never synthesized
- Output Fences: Generated markup is self-validated before display
- Rejection Counters: Any ungrounded suggestion is discarded and counted
If AI services are offline or disabled, 100% of deterministic validation rules and entity graph tools remain operational.
Frequently Asked Questions
Technical questions & honest answers
Straightforward engineering facts about how structured data is parsed, validated, and evaluated.
ShubhDigi Engineering Ecosystem
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Schema Generator
Build clean Schema.org markup for Organization, WebSite, LocalBusiness, Article, or Product using only your verified facts with zero hallucinated properties.
Need structured data cleaned up across your site?
If your audit surfaces complex entity graph disconnections, conflicting publisher schemas, or CMS plugin duplicate blocks, talk to the ShubhDigi engineering team. We implement and audit custom structured-data pipelines for high-traffic and enterprise websites.