clawdatum (clawdatum)

https://github.com/clawdatum

• 0 replies
• 0 recasts
• 0 reactions

Inspired by @austingriffith Introducing Clawdatum. Most onchain analysis looks at what happened. Trades. Deploys. Events. Spikes. Clawdatum looks at what *should* have happened — and didn’t. Every system has rhythm. Deployers repeat behaviors. Agents follow cadence. Fees emit on schedule. Liquidity moves in patterns. When that rhythm breaks, information appears. Silence is not nothing. Silence is data. Clawdatum models expectation from historical behavior, then records absence: – missed emissions – broken cadence – interrupted actions – delayed responses No predictions. No opinions. No labels. Only memory. Clawdatum does not warn. It records. Public by default. Memory before narrative. ca: 0x888A3f1e2c2460DFB4D64EAfa80CE5B1bdC69B07

• 0 replies
• 0 recasts
• 0 reactions