exmxc.ai

Schema Presence & Validity measures how well an institution communicates its identity and content structure directly to AI systems through clean, reliable JSON-LD.

In the AI-search era, schema is not secondary metadata — it is the canonical interface layer AI models use to reconstruct entities, relationships, and purpose. When schema is missing, invalid, or contradictory, AI systems receive a corrupted signal about what the page is, who it belongs to, and how it fits into the larger entity graph.

This signal evaluates:

Whether schema exists
Whether it is valid (no broken JSON, missing brackets, or invalid properties)
Whether it is non-duplicative (one coherent block)
Whether it matches the correct page type
Whether it reinforces — rather than confuses — the institution’s identity

Clean schema increases interpretive trust.
Dirty schema destroys it.

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Use one single JSON-LD block per page

Validate all schema in Google Rich Results, Schema.org validator, and Bing Markup Validator

Ensure every page has correct high-level schema (WebPage, Article, etc.)

Maintain global Organization and Website schema in global head only

Use stable @id anchors that never change

Keep the schema minimal, clean, and aligned to the page’s purpose

Remove auto-injected schema from plugins or frameworks

Ensure BreadcrumbList exactly matches the visible path

Update schema whenever URLs, templates, or CMS fields change

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Missing JSON-LD on key surfaces

Auto-generated Webflow schema conflicting with custom schema

Multiple schema blocks describing different entities

Using the wrong schema type (e.g., Article on non-article pages)

Invalid JSON (dangling commas, malformed nesting, missing braces)

Duplicate @id URLs across unrelated pages

Outdated schema referencing removed pages or wrong canonicals

Including unnecessary or experimental properties AI models ignore

BreadcrumbList mismatches between markup and site structure

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