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Get Started Free →staskh/risk-assessment
Assess risk metrics for a stock or position including volatility, beta, VaR, and drawdown analysis.
Passed 4 of 13 test cases with the skill, and 4 of 13 without it.
3 fixed3 passed either way12 still failing4 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
In the computed risk metric JSON for Disney (DIS), against which specific index ETF benchmark is stock beta calculated?
| Checked | Without skill | With skill |
|---|---|---|
| Measures beta relative to SPY | Missed | Passed |
The instructions your model reads when the skill loads.
Calculate risk metrics for stocks and positions.
Note: If
uvis not installed orpyproject.tomlis not found, replaceuv run pythonwithpythonin all commands below.
uv run python scripts/risk.py SYMBOL [--period PERIOD] [--position-size SIZE]
SYMBOL - Ticker symbol--period - Analysis period: 1mo, 3mo, 6mo, 1y (default: 1y)--position-size - Dollar amount for position-specific metrics (optional)Returns JSON with:
volatility - Historical volatility (annualized)beta - Beta vs SPYvar_95 - 95% Value at Risk (daily)var_99 - 99% Value at Risk (daily)max_drawdown - Maximum drawdown in periodsharpe_ratio - Risk-adjusted returnposition_risk - If position-size provided, dollar VaRExplain what the risk metrics mean and suggest position sizing if relevant.
numpyyfinanceAll timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.
test cases passed, vs 4 / 13 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.