Smart Incontinence Status Alert Skill | 智能失禁状态提醒技能

Automatically identifies wet clothing and abnormal excretion via visual AI. Instantly notifies caregivers to improve care for incontinent elderly, bedridden...

What to consider before installing: - The skill will upload or instruct upload of images/videos (potentially highly sensitive body-region footage) to cloud AI endpoints configured in the package. Confirm you trust the remote domain (config files reference lifeemergence.com) and that you have permission to transmit such data. - The package bundles a large shared library and an unrelated 'face_analysis' subskill — this increases code surface area. Ask the publisher why those modules are included and whether a minimal client could be provided. - Although SKILL.md forbids reading local memory, the code's config loader will create/read YAML config files and the DAO may create a local SQLite DB under the workspace (writes during import or runtime). If you require no local persistence, run the skill in an isolated environment or inspect/utilize a minimal fork that removes DAO/config write behavior. - The skill expects an 'open-id' and optionally an api-key; these may be read from workspace config or environment variables that the package will consult. Verify where credentials are stored and ensure they are not shared with untrusted services. - Before enabling this skill for real users (especially in production or with real patients), review the RequestUtil and util.py implementations to confirm exactly which endpoints, headers, and files are transmitted, and consider a controlled test with non-sensitive data. If you lack the ability to audit the code, do not install this skill in environments containing real patient data or unrestricted filesystem access. Consider requesting the publisher to supply a minimal client that only contains the incontinence analysis code and explicit, documented network endpoints and storage behavior.