Anthropic.com scores 65/100, indicating partial visibility in AI-generated answers. While AI engines can access the site, improvements in structured data and content mapping are needed to enhance visibility.
What the Probe Saw
The probe reveals that anthropic.com is partially visible to AI engines, scoring 65 out of 100. The homepage is accessible, returning an HTTP 200 status with approximately 4,660 characters of server-rendered text. This ensures that retrieval bots can read the site effectively. Additionally, major AI crawlers like GPTBot, ClaudeBot, and PerplexityBot can access key pages without restrictions. However, the absence of an llms.txt file means that AI engines lack a curated map to the site's best content, leading them to guess what is important. Furthermore, the homepage lacks a JSON-LD schema, preventing engines from understanding the type of entity anthropic.com represents. Despite these issues, the site's structure is answer-ready, with a clear H1 and five sections containing short, extractable answers.
Implications for Business Sites
For a typical business site, the findings for anthropic.com highlight the importance of structured data and content mapping. While having a readable homepage and allowing AI crawlers access are foundational, they are not enough to ensure optimal visibility in AI-generated content. The absence of an llms.txt file means AI engines are left without guidance, potentially missing key content. Implementing an llms.txt file can direct AI crawlers to prioritize important pages, enhancing visibility. Similarly, using a JSON-LD schema helps AI understand the site's nature and context, further improving its integration into AI-driven answers.
Businesses aiming to improve their AI visibility should consider using tools like our free checker to identify similar gaps. Additionally, resources such as the llms.txt guide and the AI crawler playbook provide valuable insights into optimizing site structure for AI.
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