I’ve been analyzing how different LLM agents (GPTBot, ClaudeBot, Perplexity) crawl modern marketing sites. I found that while many sites rank well on Google, they often score poorly on "LLM Readability"—meaning the agents struggle to parse the content due to hydration latency or schema gaps.
I built this tool to assign a "readability score" to your site by simulating those specific user-agents and evaluating the raw HTML response.
Tech Disclaimer (v0.1): This is currently an early MVP. I am actively developing a much more polished version (and an API) to handle edge cases and deeper rendering issues.
Right now, I’m looking for feedback on the scoring logic:
Does the score feel accurate for your tech stack?
Are there signals you think should weigh heavier (e.g., Schema vs. raw text)?
Feedback is welcome.
-- Hristo