How an AI-Agent Analytics Layer Works: Notes on Cookie.fun's Data Approach" published
If you wanted to rank AI agents in crypto, where would the data come from, and how would you stop people gaming it? Cookie DAO's Cookie.fun is a useful real-world example: it indexes 1,400+ agents by merging off-chain chatter with on-chain behavior. Here is the architecture at a conceptual level, b
Here is the architecture at a conceptual level, based on SoluLab's published case study.
The key design choice is bridging off-chain sentiment with on-chain behavior in one signal dashboard. Social data alone is easy to inflate. On-chain data alone misses attention.
* Mindshare as a ranking primitive * Mindshare ranks agents by attention-weighted activity. The weighting details are not public in the case study, so treat this as a concept rather than a formula. For builders, the useful lesson is that a ranking needs both an activity signal and an attention signal.