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RiskModels Stock Risk Snapshot

riskmodels_get_stock_snapshot
Read-only

Retrieve one US stock's end-of-day risk snapshot: SPY and sector/subsector hedge ratios, explained-risk shares, volatility, closing price, and market cap.

Instructions

Use when you need one US stock's latest risk numbers: hedge ratios to SPY and to its sector and subsector ETFs, explained-risk shares by layer, volatility, closing price and market cap. Not for a layer-by-layer decomposition or the ETF hedge of a dollar position (use riskmodels_decompose), several stocks at once (use riskmodels_compare) or daily history (use riskmodels_get_returns). Returns the latest row of GET /metrics/{ticker}, including the hedge_levels block with hedge ratios, explained risk and hedge ETFs at L1, L2 and L3. End-of-day data, refreshed after each US market close. Price: $0.005 per call.

Input Schema

NameRequiredDescriptionDefault
tickerYesUS stock ticker symbol, case-insensitive, e.g. NVDA

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.12

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the safety profile (readOnlyHint, destructiveHint=false, openWorldHint), and the description adds material context beyond them: end-of-day freshness refreshed after each US market close, the underlying GET /metrics/{ticker} endpoint and that it returns the latest row including the hedge_levels block, and a per-call price of $0.005. Freshness and cost are exactly the operational traits annotations cannot express.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with the positive trigger before the negative routing, then return shape, then freshness and price. Every clause carries information an agent needs; nothing is padding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description carries the return burden and does so — it names the endpoint, the returned row, and the hedge_levels block at L1/L2/L3. Combined with freshness and pricing, an agent has everything needed to call it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the single ticker parameter is fully documented there (case-insensitive, e.g. NVDA). The description only reinforces the 'one US stock' scope, which is already implied by the schema and the tool name, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('one US stock's latest risk numbers') and enumerates the exact contents: hedge ratios to SPY/sector/subsector ETFs, explained-risk shares, volatility, price and market cap. It also names the sibling tools it is NOT for, so an agent can distinguish it without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Opens with an explicit 'Use when you need...' trigger and then gives three concrete exclusions with the correct alternative for each: layer decomposition and dollar-position ETF hedge → riskmodels_decompose, multiple stocks → riskmodels_compare, daily history → riskmodels_get_returns. This is a complete routing rule set.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.