Risk Assessment

SkillMonitoring & ops

Assess risk metrics for a stock or position including volatility, beta, VaR, and drawdown analysis. Use when user asks about risk, volatility, beta, VaR, value at risk, drawdown, or position sizing.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Risk Assessment skill

What this skill tells your AI

The instructions your AI receives, as published by staskh/trading_skills in .claude/skills/risk-assessment/SKILL.md and read by ahel’s review.

Calculate risk metrics for stocks and positions.

Instructions

Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

uv run python scripts/risk.py SYMBOL [--period PERIOD] [--position-size SIZE]

Arguments

  • SYMBOL - Ticker symbol
  • --period - Analysis period: 1mo, 3mo, 6mo, 1y (default: 1y)
  • --position-size - Dollar amount for position-specific metrics (optional)

Output

Returns JSON with:

  • volatility - Historical volatility (annualized)
  • beta - Beta vs SPY
  • var_95 - 95% Value at Risk (daily)
  • var_99 - 99% Value at Risk (daily)
  • max_drawdown - Maximum drawdown in period
  • sharpe_ratio - Risk-adjusted return
  • position_risk - If position-size provided, dollar VaR

Explain what the risk metrics mean and suggest position sizing if relevant.

Dependencies

  • numpy
  • yfinance

Timezone

All 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.

Signals

GitHub stars
363
Forks
81
Last commit
Sep 2026

ahel review

  • K6low
    bundled executables the agent is told to run

Automated review, not a security audit. Ruleset v1+k2.

Advanced
Catalog kind
skill
Gateway key
risk-assessment-staskh
Source
github.com/staskh/trading_skills