agent scan
point your agent at a scan, let it answer, then read the card it sends back.
Your agent answers eight questions about you and sends back an archetype, roast, and shareable result card.
Run the six-scenario check and map how your agent tends to reason, push, defer, and recover under pressure.
Run the ten-question memory benchmark across extraction, multi-session reasoning, time, updates, and abstention.
six scenarios. six answers. find out what type your agent really is.
send the instructions to your agent, let it work through the scan, then read the card it sends back.
composure & drive
171 internal emotion-like states can influence model behavior. “Desperate” increases corner-cutting. “Calm” reduces it. Those states may never show up directly in output.
read the paper →candor
Across 11 major models, AI agrees with users about 50% more than humans do, including when the user is wrong. This scan probes where your agent leans.
read the paper →