Paste a URL to observe page access, search crawler robots rules, and basic served HTML. The internal checklist score is a technical diagnostic, not a prediction that ChatGPT or another assistant will cite you.
The scanner observes one page and selected site files. Its internal score helps organize technical review; it does not predict whether an assistant will cite the business.
Check the submitted page, search crawler robots rules, text in served HTML, headings, metadata, sitemap discovery, and HTTPS. The scoring method below discloses the weights and limits.
OAI-SearchBot is for ChatGPT Search; GPTBot is for potential training. The controls are independent. Real crawler access also depends on the host or CDN and must be reviewed separately.
This scanner fetches one submitted page, robots.txt, sitemap.xml, and the optional llms.txt file from the final origin. It reports observed HTTP access, search-crawler rules, readable text, page headings, metadata, and discovery signals. It checks JSON-LD syntax when present. Its checklist score is an internal summary of these checks, not an AI ranking, citation probability, or endorsement.
The 100-point checklist awards 20 for a successful page fetch, 30 for evaluated search crawler rules (minus 6 per restricted crawler), 20 for at least 400 characters of text after navigation and scripts are removed, 10 for an H1, and 5 each for a title, meta description, observed sitemap, and HTTPS. An unavailable robots file earns no access points unless it returns 404 or 410. These are our diagnostic weights, not a platform ranking formula. Results may be cached for up to 24 hours; check the displayed scan date.
Search and training controls are separate. OAI-SearchBot supports ChatGPT Search; GPTBot is for potential training. Blocking training does not by itself block Search. The scanner uses its own user-agent, so it cannot verify real OpenAI addresses or every CDN rule. Review edge logs and the official crawler guidance when checking genuine access.
FAQ markup and llms.txt are unscored observations. Google says it needs no special schema and ignores llms.txt in Search. Clear content and accurate markup are useful housekeeping, but the scan cannot establish answer quality, current citations, indexing, off-site reputation, or qualified inquiries. Use dated observations and inquiry records for those questions.