Child Learning Behavior Analysis Tool | 孩子学习行为分析工具

Conducts video analysis of learning behavior for children/students, identifies poor learning habits, provides structured analysis reports and family educatio...

Before installing or enabling this skill consider the following: - The skill will accept videos and upload them to remote analysis APIs. Default production endpoints are present in the bundled config (lifeemergence/open.lifeemergence.com). If you do not trust that endpoint, do not upload sensitive videos. - The manifest declared no required env vars or config files, but the skill reads workspace config files and environment variables (OPENCLAW_WORKSPACE, OPENCLAW_SENDER_OPEN_ID, etc.) and will create/use a local SQLite database under the workspace. Expect persistent storage of uploaded videos and reports in the agent workspace/data and attachments folders. - The package bundles a large common library (smyx_common) and an unrelated face_analysis module; this increases the attack surface and means the skill can access generic utilities (HTTP, DB, filesystem) beyond narrow video-analysis code. - If you proceed: (1) review/override the skill config to point to an endpoint you control or a vetted service; (2) run the skill in an isolated workspace (not containing other sensitive files) and set OPENCLAW_WORKSPACE to an empty folder; (3) do not enable it to process videos containing private or identifying content unless you accept the upload to the remote server; (4) verify where attachments and DB files will be stored and periodically inspect/clean them. Because of the mismatches between declared metadata and actual behavior (filesystem writes, env reads, external uploads, extra modules), treat this skill as suspicious and only enable it after you have validated the endpoint and workspace configuration.

Type: OpenClaw Skill Name: smyx-study-analysis Version: 1.0.1 The skill bundle provides a comprehensive tool for analyzing children's learning behavior via video, utilizing a cloud-based API (lifeemergence.com). It includes a robust shared utility library (smyx_common) that handles authentication, local token caching in a SQLite database, and structured API communication. The SKILL.md file contains strict 'Forced Memory Rules' designed to ensure the AI agent retrieves historical data exclusively from the cloud API rather than potentially stale local memory files, which serves as a functional constraint rather than a malicious injection. No evidence of unauthorized data exfiltration, malicious execution, or deceptive behavior was found; the code is well-structured and aligned with its stated educational purpose.