Pet Daily Health Monitoring & Analysis Tool | 宠物日常健康监测分析工具

Based on computer vision, analyzes pet health indicators such as feeding frequency, drinking frequency, excretion status, mental state, vomiting behavior, an...

Key points to consider before installing/running this skill: - The skill does perform the advertised CV→API analysis, but it also expects to read local configuration files (skills/smyx_common/scripts/config.yaml and workspace-level config) and may use environment variables like OPENCLAW_WORKSPACE and OPENCLAW_SENDER_OPEN_ID. These are not listed in the skill's declared requirements — confirm where open-id/api-key values will come from before running. - The code contains a local SQLite DAO that will create/read a database under the workspace (workspace/data/smyx-common-claw.db). If you do not want persistent local records or files in your workspace, run it in a sandbox or container and inspect/clean the workspace afterward. - SKILL.md forbids reading local 'memory' files, yet the codebase has modules for local storage and utilities. That inconsistency should be resolved with the author. Ask the author: do you store any user/report data locally? Under what conditions is local DB used versus cloud API? - Network endpoints: the included common config points at lifeemergence.com (and dev/test endpoints). If you must run this, verify the API base URLs (and the trustworthiness of those servers) and avoid supplying sensitive credentials to an untrusted endpoint. - Dependency surprise: the repository lists many Python packages (skills/smyx_common/requirements.txt). Running the scripts may require installing them. Prefer to run in an isolated virtualenv/container and review the code paths that perform HTTP requests (RequestUtil) and file writes before giving it real videos or private identifiers. - Minimum actions to reduce risk: inspect and, if needed, edit config YAMLs to point to a trusted API endpoint or to remove/neutralize production endpoints; supply a non-sensitive test open-id; run the tool in a disposable environment; review RequestUtil implementation to see what headers/credentials are sent; and ask the publisher for a homepage/source provenance and privacy policy. If you want, I can: (a) list exact files/lines that read env vars and write DB/files, (b) summarize network request construction (endpoints/paths) found in the code, or (c) produce a safe checklist to run the skill in a container.