GEO / AI Discoverability

Tureka AI Visibility Checker uses this page to explain how this signal affects AI visibility reports and which implementation details matter most.

Generative Engine Optimization focuses on whether AI-powered answer systems can discover, parse, trust, and cite a source. It is not a promise of placement.

The MVP checks AI crawler access, llms.txt, machine-readable identity files, structured data, content clarity, crawl-safe infrastructure, and emerging agent discovery signals.

Crawler checks cover Googlebot, Bingbot, GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot, Claude-User, PerplexityBot, Applebot, Applebot-Extended, Google-Extended, and CCBot.

The scanner now scores llms.txt quality, Content-Signal directives, RFC 8288 Link headers, Markdown for Agents negotiation, API catalogs, MCP discovery files, Agent Skills indexes, and lightweight WebMCP signals.

OAuth/OIDC, protected resource metadata, and auth.md are treated as optional signals. They help API products, but their absence should not heavily penalize ordinary content websites.

For AI agents, Tureka also publishes x402-paid package endpoints under /api/x402. The public website scan under /api/scans remains free and separate from the agent payment layer.

Reports now show coverage and confidence so teams can separate a strong technical signal from a narrow scan.

Criteria covered here

AI crawler access is not explicitAI crawler access is not explicitContent Signals are missingAgent discovery Link headers are missingMarkdown response for agents is missingWebMCP signal is not visible in raw HTMLllms.txt is missingllms.txt is thin or missingAI discovery files are thin or missingrobots.txt does not reference a sitemap