# Risk Scoring

> Score how concentrated and risky a portfolio is on a 0-100 scale from its position weights. Use when the user asks how risky their portfolio is, whether it is too concentrated, or for a diversification check.

- Skill: `azure-ai-foundry/risk-scoring` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add azure-ai-foundry/risk-scoring`
- Raw SKILL.md: https://api.skillmd.com/api/skills/azure-ai-foundry/risk-scoring/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: azure-ai-foundry (https://skillmd.com/u/azure-ai-foundry)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/azure-ai-foundry/risk-scoring

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## Usage

When the user asks about portfolio risk or concentration:

1. Read `references/risk-bands.md` to understand the score bands and what drives them.
2. Compute each holding's market value (shares × price) — use the `get_stock_price` tool for current
   prices if you do not already have them.
3. Run `scripts/risk_score.py` with one `--position VALUE` argument per holding,
   e.g. `--position 18518 --position 17201 --position 16177`.
4. Report the 0-100 score, the band it falls in, and the largest single-position weight, then suggest
   (in general terms) whether the portfolio looks well diversified or concentrated.

Remind the user this is a crude concentration measure, not a complete risk model, and not advice.