ai-readability-audit

AI readability auditing evaluates how AI systems interpret your website by analyzing metadata, JSON-LD schema, Open Graph tags, and semantic HTML. Provide your site URL to generate a structured report with actionable recommendations for improving AI understanding and extraction accuracy.

The audit examines JSON-LD, Open Graph metadata, semantic HTML tags, page titles, headings, and structured data markup. It assesses how these elements communicate content meaning to AI tools and LLMs, identifying gaps that cause misinterpretation.

Structured data like JSON-LD and Open Graph provides explicit, machine-readable content context. Without it, AI systems must infer meaning from raw HTML, leading to incomplete or inaccurate summaries. Clear markup ensures AI tools extract your intended information reliably.

Yes, the audit works across marketing, content, and product pages. It evaluates semantic structure and metadata on any page type to ensure AI systems accurately understand and represent your content in search, summaries, and AI assistant responses.

The audit generates a prioritized report with structured findings, identified gaps in metadata and semantic markup, and a remediation plan. It provides actionable recommendations for developers and content teams to improve AI readability incrementally.