Schema Markup Checker for LLMs
Schema markup is the language AI systems use to understand your content. Glippy validates your Schema.org implementation and checks whether your markup provides the structured information that LLMs need to accurately interpret and cite your pages.
Schema Markup and LLM Comprehension
Large language models use schema markup as a structured signal to understand page content. While LLMs can read natural language, structured data provides unambiguous machine-readable context about content type, authorship, dates, and relationships.
Key Schema Types for LLM Optimization
- Article / BlogPosting - Identifies editorial content with author, date, and topic
- FAQPage - Structures Q&A content for direct answer extraction
- HowTo - Step-by-step instructions that LLMs can present as guides
- Product - Product details including price, availability, and reviews
- Organization / Person - Entity identity for authority signals
- SpeakableSpecification - Content suitable for voice and AI reading
Common Schema Issues Glippy Finds
Many websites have incomplete or incorrect schema markup. Glippy checks for missing required properties, incorrect nesting, orphaned schema blocks, and missed opportunities for schema types that would help LLMs better understand your content.
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