The strongest proof we can offer: we wrote the methodology out in the open, we built the audit, and we run it on our own website every month. The score above is what the tool told us this month — refreshed monthly.
Ahead of most. Vulnerable to the next competitor that figures it out.
Last audited: 2026-05-22 · Run the same audit on your site
Before we made the 17 fixes, Brandermind itself scored 47/100 — squarely in the Developing tier. Plenty of marketing copy about AI; very few of the signals AI agents actually look for.
The fixes were the same ones we now do for clients: Schema.org graph repairs, FAQ markup on every service and industry page, llms.txt, per-route lastmod, AggregateRating wired into Organization schema, sameAs links to verified profiles.
The result: a 31-point lift into Competitive tier — and a 8-point drop the day we shipped probes for three new 2026 cross-platform agent standards (A2A, UCP, WebMCP). We're publishing the drop in the open rather than freezing the rubric to keep the number high. The same playbook works on your site.
Five pillars. 20 points each.
The Schema.org markup that lets agents extract facts before they read prose.
Readable, extractable answers — the substrate AI agents quote.
The machine-readable surface AI agents talk to — llms.txt, sitemaps, feeds, public endpoints, and the 2026 cross-platform standards (A2A, UCP, WebMCP).
How clearly your reputation is declared in your site's schema and content — what agents can parse without leaving your domain.
How recently you've shown agents you're still here — and still right.
We didn't grade ourselves. The same public audit engine that scores client sites scored this one. The methodology is published, the engine is open, and your audit uses the same scorecard.