This runs Z-score anomaly detection on Cognitum Seed device telemetry and classifies what it finds into six types: spikes, flatlines, drift, oscillation, pattern breaks, and cluster outliers. You pass in a device ID and it pulls recent data, scores the anomalies, and can flag devices for quarantine if the score breaks 0.9. It also stores patterns to memory so Claude can learn from past incidents. Useful if you're managing IoT fleets and need to catch hardware failures or sensor drift before they cascade. The detection happens through an npx package, so nothing to install permanently.
npx skills add https://github.com/ruvnet/ruflo --skill iot-anomalies