AI search visibility, LLM discoverability, AI crawler access, metadata, llms.txt, structured data, and AI-ready technical SEO — described carefully, without invented ranking factors.
AI discoverability rests on the same fundamentals as classic SEO: accessible HTML, clear structure, valid structured data, and a clean crawl graph. These resources explain what commonly helps — and what no one can promise.
The synthesis reference for crawlability, structured data, internal linking, content quality, and the AI crawler ecosystem.
Read the complete guide →Reference for GPTBot, OAI-SearchBot, and ChatGPT-User — the three OpenAI user-agents with independent opt-outs.
Read the complete guide →Reference for PerplexityBot and content patterns that may support inclusion in Perplexity's citations.
Read the complete guide →How Anthropic's Claude ecosystem may interact with web content, and why "Claude SEO" is the wrong frame.
Read the complete guide →The community convention, what it is and what it is NOT, structure, validation, and relationship to sitemap.xml and robots.txt.
Read the complete guide →Per-crawler reference for GPTBot, ClaudeBot, PerplexityBot, Google-Extended, Applebot-Extended, Meta, Bytespider, CCBot — DOCUMENTED facts vs. RECOMMENDED practice.
Read the complete guide →Where SEO and AI discoverability converge.
Open →Technical best practices overview.
Open →Crawler access and clean structure.
Open →Being a citable source.
Open →Robots rules and accessibility.
Open →A readable map for LLMs.
Open →Step-by-step guide.
Open →Owned analytics for visibility context.
Open →Related: guides · technical SEO · AI search · integrations · tools · docs · WebmasterID.