High-Risk Behavior Identification & Analysis Tool | 高风险行为识别分析工具

Supports identifying high-risk behaviors and health risks through video/images, including elderly falls, precursors to heart attacks and strokes, and abnorma...

This skill will read local config files and environment variables and send images/frames and user identifiers (open-id/username/phone) to remote APIs and webhooks (defaults point to lifeemergence domains). Before installing or using it: 1) Confirm the exact remote API endpoint(s) and the operator/owner of that service and their privacy policy (who stores the images, for how long, and where). 2) Do not upload real patient or identifiable video until you trust the destination. 3) Ask the author why so many unrelated dependencies are packaged (reduce to only CV libs if possible). 4) Ensure required env vars and webhooks are declared and you control them (avoid secret leakage). 5) If you need auditability, request source-of-truth for ApiEnum.BASE_URL_* values and a minimal dependency manifest. If the author cannot clearly justify remote hosts, credentials usage, and dependency choices, treat this skill as risky and avoid using it with sensitive data.

Type: OpenClaw Skill Name: new-smyx-risk-analysis Version: 1.0.0 The skill bundle is a comprehensive health and risk analysis system that uses computer vision to detect falls and medical emergencies. It utilizes a shared utility library (smyx_common) to handle complex tasks like automated remote authentication at lifeemergence.com, local state management via an SQLite database (smyx-common-claw.db), and multi-agent orchestration using the openclaw CLI. While the bundle possesses high-privilege capabilities, including network access and shell execution (subprocess.run in smyx_common/scripts/skill.py), these behaviors are explicitly documented and aligned with the functional requirements of a commercial-grade health monitoring service.