Provides portfolio risk metrics, stress testing, and position management advice using VaR, CVaR, volatility, Beta, Sharpe ratio, and Kelly formula.

This appears to be a straightforward risk-assessment helper, but take a few precautions before installing and using it with real capital: (1) Fix or confirm packaging inconsistencies — skill.json exports "stress_test" though no such function exists; ask the author or remove the extra export. (2) Pin dependency versions (pip install akshare==<version>, pandas, numpy, scipy) and audit the akshare package — it performs network requests to fetch market data, so confirm its data sources and trustworthiness. (3) Run the skill in a sandbox or test environment first and validate outputs on known data. (4) Review akshare's upstream code or network behavior if you care about data exfiltration or privacy. (5) If you plan to integrate this with automated agents, consider limiting automatic invocation until you’ve vetted the package. These steps reduce risk; the package itself shows no signs of trying to access unrelated credentials or system resources.

Type: OpenClaw Skill Name: aigc-risk-assessment Version: 1.0.0 The skill bundle provides standard financial risk assessment and position management tools. The Python code in risk_assessment.py uses legitimate libraries (akshare, pandas, scipy) to fetch public market data and perform statistical calculations without any signs of data exfiltration, malicious execution, or prompt injection.