Smart Baby Cry Analysis Skill | 婴儿哭声智能解析技能

Detects baby cries via audio AI in real-time, analyzes causes, and precisely identifies needs like hunger, tiredness, pain, discomfort, or irritability to as...

What to consider before installing or running this skill: - Data exfiltration: The skill uploads user-provided audio/video to a remote API (configuration points to lifeemergence/open API domains). If you will send private baby recordings, confirm you trust that remote service and understand its data retention and privacy policy. - Local writes: Importing/running the code may create config.yaml files and a local SQLite DB under your workspace (smyx_common.YamlUtil will create missing config files; dao.py writes under workspace/data). If you want no disk persistence, do not run it or inspect/run in an isolated environment. - Inconsistent rules: SKILL.md forbids reading local memory but the codebase contains local DB utilities and will read environment variables (OPENCLAW_SENDER_OPEN_ID, OPENCLAW_WORKSPACE). The documentation’s 'open-id retrieval' sequence and the CLI implementation do not match — verify how open-id/api-key are actually obtained before use. - Minimal principle: The repository contains unrelated/extra modules (face_analysis, large common libs). Ask the provider why those are bundled; prefer a minimal implementation or request a version that contains only the cry-analysis code. - Testing advice: Run in an isolated VM/container, monitor outbound network calls (which endpoints are contacted), and inspect any files created under your workspace before sending real user data. If you cannot confirm the destination/service operator, do not upload sensitive recordings. If you want, I can list the exact files and code locations that: (1) write config files, (2) build the local DB path, and (3) contact external endpoints so you can audit them or block them in a test run.

Type: OpenClaw Skill Name: smyx-infant-cry-analysis Version: 1.0.0 The skill bundle provides infant cry analysis by interfacing with a cloud-based AI service (hosted on lifeemergence.com). It utilizes a shared utility library (smyx_common) that manages authentication, including local token persistence in a SQLite database (smyx-common-claw.db) and automated login via a health-check endpoint. While the SKILL.md contains 'Mandatory Memory Rules' that instruct the AI agent to ignore local session history in favor of cloud-retrieved data, these appear to be functional requirements for data synchronization rather than malicious prompt injection. The code follows standard patterns for API interaction and lacks indicators of intentional harm or unauthorized data exfiltration.