coindesk.com — AI Search Visibility Report
Overall score: 84/100
AI search visibility analysis for coindesk.com. LLMao scored coindesk.com 84/100 across 8 LLM-readiness categories including crawlability, semantic content, structured data, authority signals, and answer-engine clarity.
Analyzed URL
Category breakdown
- readability: 80/100 — High clarity and professional jargon handling, though some financial sentences are dense.
- schema_markup: 70/100 — JSON-LD is present but primarily focused on WebSite/Organization; lacks deep Article/Person schema on the homepage feed.
- authority_trust: 85/100 — Strong trust signals with clear contact info and social proof, but editorial standards are not explicitly linked in the footer.
- citation_sources: 90/100 — Excellent attribution to primary sources (FT, TradingView, Getty) and clear claim verification.
- content_freshness: 100/100 — Exceptional freshness with multiple updates per hour and clear 2026 timestamps.
- content_structure: 75/100 — Good use of semantic HTML, though heading hierarchy on the homepage is slightly flat.
- entity_definition: 70/100 — Brand consistency is high, but author entities are not fully defined on the homepage.
- technical_accessibility: 85/100 — Excellent meta descriptions and social meta; robots.txt is standard but lacks specific AI bot directives.
Top recommendations
- Enhance Author Entity Schema (Schema Markup): Implement Person schema for all authors mentioned in the news feed to help LLMs build a knowledge graph of expert contributors.
- Formalize Editorial Standards Visibility (Authority & Trust Signals): Add a visible 'Editorial Standards' or 'Ethics Policy' link in the footer to satisfy LLM trust requirements for news organizations.
- Optimize Heading Hierarchy in News Feed (Content Structure): Ensure the main news feed uses H2 tags for article titles instead of just anchor tags to improve semantic hierarchy.
- Update AI Crawler Permissions (Technical Accessibility): Explicitly allow PerplexityBot and ClaudeBot in robots.txt to ensure optimal indexing by the latest LLM search engines.
- Implement Technical Glossary Entity Schema (Entity Definition): Create a dedicated glossary or 'Term Definitions' section for complex crypto jargon (e.g., 'Clear Signing', 'Alpenglow upgrade') to improve RAG performance.