Forecast Valuation

Things to consider before installing or running this skill: - The main functionality (creating Excel valuation models) is implemented in the included build_forecast.py; that matches the description. However the README/SKILL.md references other helper scripts (build_dcf.py, build_comps.py, test_connection.py) that are not present. Ask the author for the missing scripts or avoid commands that call them. - The configure.py will prompt you to enter API keys and will save them into a local config.json file inside the skill directory. If you provide real API keys, they will be stored on disk in plaintext — consider using temporary/test keys, storing secrets in a secure location, or editing the script to read from protected environment variables instead. - The script defaults OUTPUT_DIR to /root/.openclaw/workspace. Running as a non-root user may fail or will create files under /root; check and change OUTPUT_DIR before running if needed. - The code uses network-capable libraries (requests) and SKILL.md says it will fetch market data (10-year yield) and pull from Gangtise/Tushare. Review the remaining (truncated) portions of build_forecast.py to confirm which external endpoints it contacts, and whether any endpoints are unexpected. Run the code in a sandboxed environment (isolated VM or container) if you cannot verify those calls first. - No automated installer downloads code from arbitrary URLs (good), but because this skill comes from an unknown source (no homepage) you should inspect the complete scripts locally before executing them. If you decide to use the skill, prefer manual credential handling (do not reuse high-value production keys) and limit file permissions on config.json (chmod 600) or move secrets into environment variables/secret manager.