Detect and classify unusual readings from Cognitum Seed devices, including spikes, flatlines, and drift. Review anomaly scores, recommend quarantine for scores above 0.9, and save detected patterns for future reference.
Detect and classify telemetry anomalies on Cognitum Seed devices. Use when investigating a device that's reporting odd metrics, before approving a firmware canary advancement, or when triaging fleet-wide health alerts.
Examines recent telemetry from a Cognitum Seed device and reports anomaly types and scores. It uses Z-score detection, which measures how far readings differ from usual values. It classifies spikes, flatlines, gradual drift, oscillation, broken patterns, and readings that stand apart from a group. When a score exceeds 0.9, it recommends quarantining the device. Detected types and scores are saved to memory.
Use it when a device reports unusual readings or when you need to triage health alerts across many devices. It also supports checks before advancing a firmware canary rollout, where firmware is first tried on a subset of devices.
Requires a device ID and @claude-flow/plugin-iot-cognitum@1.0.0, run through npx. Recording results uses the memory-storage MCP tool from ruflo-core. The workflow recommends quarantine; it does not include automatically quarantining devices.
This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.
AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.
The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 21, 2026. Treat it as a guide and read the original before installing.
Review the instructions the agent will receive before you install.
Run Z-score anomaly detection on a device's recent telemetry.
Steps:
npx -y -p @claude-flow/plugin-iot-cognitum@1.0.0 cognitum-iot anomalies DEVICE_IDmcp__plugin_ruflo-core_ruflo__memory_store({ key: "iot-anomaly-DEVICEID", value: "TYPE at SCORE", namespace: "iot-anomalies" })No reviews yet. Tell others what you thought.
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