The web is going machine-first: AI agents and answer engines are becoming the visitors that matter. This free agent-readiness scorecard checks whether your site can be discovered, read, and trusted by them — scoring signals like llms.txt, structured data, entity markup, and AI-crawler access.
How the agent-readiness scorecard works
Enter any public URL. The tool fetches the page along with its robots.txt and llms.txt, then scores ten machine-first signals: an llms.txt file, JSON-LD structured data, Organization schema, a verified entity (sameAs), whether AI crawlers are allowed, Open Graph metadata, a canonical URL, a sitemap or feed, HTTPS, and a clean single H1. The higher your score, the easier it is for AI agents and answer engines to use your site as reliable infrastructure.
Frequently asked questions
What does agent-readiness mean?
Agent-readiness is how well your site can be found, parsed, and trusted by AI agents and answer engines rather than human browsers. As more discovery and buying happens through AI, machine-readable structure, identity, and access become as important as traditional SEO.
What is an llms.txt file?
llms.txt is a plain-text file at your domain root that gives AI systems a curated map of your most important content, similar to how robots.txt guides search crawlers. It is an emerging convention for the machine-first web.
Should I let AI crawlers access my site?
If you want to appear in AI answers and be usable by agents, generally yes — blocking crawlers like GPTBot or Google-Extended in robots.txt removes you from those surfaces. The scorecard flags when AI crawlers are disallowed.