Trading Quant

This skill appears to implement a real trading-analysis tool, but review these things before installing or running it: - Watchlist / external file access: industry_classifier tries to read a file at a relative path that escapes the package (../../../../..../knowledge/watchlist.json). That will access files outside the skill bundle if present — verify what that path would resolve to in your environment and ensure it won't read sensitive data. - Model downloads and network: the sentiment module can download HuggingFace models at runtime (large files and outbound network calls). If you need to restrict network or disk usage, run the skill in a sandbox/container, or pre-populate the model cache. - Persistent files: it writes caches to /tmp, ~/.cache/huggingface, and a workspace directory (~/.openclaw/workspace-trading by default). Clean these if you uninstall or run in an ephemeral environment. - No credentials requested: the skill doesn't require API keys or secrets in its metadata. However, the code relies on public data sources (Tencent, Sina, EastMoney, akshare, yfinance). If you plan to integrate private credentials later, inspect where those would be provided. - Dependency management: requirements.txt exists but no installer is provided. Pin and review Python package versions before pip installing; consider using a virtualenv. If you are uncomfortable with the external-file reads or model downloads, run the skill only in an isolated/containerized environment, or ask the author to remove or make explicit the watchlist-prefill behavior and to document expected network and disk usage.