Micro-Doppler Life-Safety Engine

Detects elder falls and apnea using privacy-safe 60/77 GHz mmWave radar with real-time micro-Doppler STFT analysis for emergency alerts and response.

This skill appears to do what it says: run a local DSP fall detector and optionally send commands to Home Assistant. Before enabling real actuation: 1) Keep S2_ENABLE_REAL_ACTUATION unset (Dry-Run) while you review and test behavior. 2) If you enable real actuation, only do so in a trusted, local network. 3) Create a Home Assistant token with minimal scope needed for the specific entities, and verify HA_BASE_URL points to your local instance. 4) Inspect and, if necessary, change the entity IDs (lock.room_802_main_door, light.room_802_all, fan.room_802_hvac) so they map to test devices first (avoid unlocking real doors during testing). 5) Confirm the manifest/registry metadata (homepage and declared env vars) with the publisher because the packaged manifest includes env var docs that the registry metadata did not list. If you want extra assurance, run the script in an isolated environment or sandbox and keep network access to your HA instance restricted.

Type: OpenClaw Skill Name: s2-eldercare-mmwave-monitor Version: 1.1.0 The skill implements mmWave-based fall detection and physical emergency response via Home Assistant integration. While it includes a 'Dry-Run' safety mechanism and clear documentation in SKILL.md and skill.py, it possesses high-risk capabilities such as the ability to unlock physical doors (lock.unlock) and control HVAC/lighting systems via network requests. These behaviors are aligned with the stated purpose but fall under the 'suspicious' category due to the inherent risk of physical actuation by an AI agent, despite the lack of evidence for malicious intent or data exfiltration.