Stop Asking Whether Schema Exists. Ask Whether the Entity Graph Actually Makes Sense.
Aegisify Schema Intelligence audits the JSON-LD graph generated for published WordPress content, measures schema health and knowledge-graph readiness, finds missing critical fields and broken @id relationships, ranks weak pages, previews exact output, and supports bounded non-destructive render-time fixes.
NodesEdgesRefsCoverage
Build a Baseline, Find Weak Graphs, Fix Safely, Then Rescan
The workflow is incremental by design: establish a full baseline, update changed content, inspect severity and connectivity, then validate the generated graph after any fix.
Click a stage to expand
01Full Scanbaseline
02Update Scanincremental
03Diagnosenodes + edges
04Scorehealth + KG
05Fix Safe Gapsrender-time
06Validateexact JSON-LD
Inspect More Than Schema Type
Each analyzed page is reduced to measurable graph properties so weak structured data can be prioritized consistently.
What Entities Exist?
Aegisify inventories @id-bearing nodes and counts schema entity types generated for the page. Organization and WebSite form important identity baselines, while page-specific entities may include Article, BlogPosting, FAQPage, HowTo, Product, Event, and other supported types.
Do Relationships Resolve?
The analyzer walks nested schema values looking for @id references, records relationships between entities, and flags targets that do not exist in the current graph. Broken references increase page severity because the graph points to an entity it never defines.
Are Entities Actually Connected?
Aegisify measures average, minimum, and maximum degree plus isolated nodes. Low connectivity can reveal page, author, publisher, or mainEntity relationships that exist as separate objects but do not form a coherent graph.
What Important Evidence Is Absent?
Article-like nodes are reviewed for fields such as headline, description, image, author, datePublished, and mainEntityOfPage. The audit also checks for Organization and WebSite baselines and records recommended schema coverage gaps.
Schema Health and Knowledge Graph Readiness Answer Different Questions
Aegisify keeps syntax/quality pressure separate from the strength of the site’s connected entity foundation.
Missing, Broken & Severe
The site-level Schema Health score starts from 100 and is reduced by average page severity, accumulated broken references, and prevalence of missing critical fields. It is bounded to 0–100 and exists to prioritize remediation.
Identity + Diversity + Connectivity
The readiness index awards weight for Organization and WebSite presence, entity-type diversity, and average graph connectivity. It measures Aegisify’s structured-data foundation, not whether a search engine has built or accepted a knowledge panel.
Explainable 0–100 Risk Signal
Per-page severity increases with missing critical fields, broken references, isolated nodes, and weak average degree. Pages with higher severity or low connectivity are surfaced as weak pages for review.
See Entity Coverage, Hubs, Weak Pages, and Broken Connections
The report aggregates per-page graphs into a site-level structured-data quality review.
The Entity Coverage Report shows which schema types appear across the scanned baseline. Structural Connectivity Analysis summarizes graph density and relationship health. Missing Field Audit aggregates recurring critical and recommended gaps, while the Broken Reference Audit exposes unresolved @id targets that can fragment machine-readable relationships.
Aegisify also identifies Top Entity Hubs and Weakly Connected Pages. Weak pages are selected when severity is high or average graph degree is low, then sorted by severity so the largest structural problems appear first. A full drilldown table exposes post type, title, URL, missing fields, broken references, severity, and connectivity for auditing or client QA.
Current report data and the full drilldown can be exported to CSV or JSON. Those exports make the intelligence useful outside the WordPress screen for QA, change documentation, or structured-data review programs without requiring teams to scrape the admin interface.
Improve Generated JSON-LD Without Editing Page Content
The current safe-fix workflow is intentionally narrow and non-destructive.
Reconnect Primary Content
Where supported, Aegisify can inject missing mainEntityOfPage relationships from the generated WebPage entity so the primary content node links back to the page it describes.
Restore Identity Relationships
The fix layer can use configured fallback author information and enforce publisher/Organization relationships when those links are missing from generated output.
Use Existing WordPress Evidence
Supported fallbacks can draw from title, excerpt, and featured-image evidence. The engine enriches JSON-LD at render time instead of changing the visible post body.
Estimate Before Enabling
Aegisify counts currently fixable missing fields and estimates a bounded potential improvement to its own diagnostic scores. The interface tells administrators to run Update Scan afterward because actual results must be measured.
Inspect the Exact JSON-LD Aegisify Generates
Site-level scores are useful for prioritization; page-level output is what needs to be validated.
The Schema Graph Preview + Validator lets an administrator choose published content, build the actual Aegisify schema graph, and inspect the JSON-LD directly. A visual graph is also available as an optional exploration and presentation layer with focused or type-cluster modes, edge controls, labels, neighbor highlighting, and PNG export.
Aegisify explicitly tells users to rely on the intelligence sections for SEO decisions and use the visual map as an exploration aid. The JSON-LD preview can then be tested with external validators for independent syntax and rich-result checks.
Build the Baseline, Fix the Weak Graphs, and Rescan
Use Aegisify Schema Intelligence to move from schema presence to entity coverage, relationship quality, safe remediation, and verifiable generated output.
Common Questions About the Analyzer
Is the Schema Health Score a Google score?
No. It is an Aegisify diagnostic calculated from generated schema severity, missing critical fields, broken references, and related graph-quality evidence.
Does Knowledge Graph Readiness mean Google will create a Knowledge Panel?
No. The index measures Organization/WebSite identity, schema-type diversity, and connectivity in Aegisify’s generated graph. Search engines make their own interpretation and display decisions.
Does Fix All Safe Issues edit my post content?
The supported Schema Intelligence fixes are described as non-destructive render-time JSON-LD enrichment. Administrators should still run Update Scan and validate important pages after enabling them.
What is the difference between Full Scan and Update Scan?
Full Scan establishes the baseline. Update Scan refreshes content modified after the stored baseline so ongoing review can be more efficient.
How can Aegisify AI help?
Ask about Aegisify or WordPress: errors, plugins, security, SEO, compatibility, troubleshooting, comparisons, or launch a free website scan.