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78degrees

QuantRisk-MCP-Server

analyze_risk

Assess portfolio risk exposure by calculating VaR, CVaR, volatility, beta, and maximum drawdown.

Instructions

Calculate core risk metrics for a portfolio — Value at Risk (VaR), Conditional VaR (CVaR), volatility, beta, and max drawdown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
positionsYesArray of portfolio positions. Each entry needs a ticker and quantity. Free tier: max 20 positions. Paid tier: up to 500.
confidence_levelNoVaR confidence level as a decimal, e.g. 0.95 = 95%. Range: 0.01-0.99. Default: 0.95.
horizon_daysNoRisk horizon in trading days. 1 = overnight, 21 ≈ 1 month, 252 ≈ 1 year. Default: 1.
methodNoVaR calculation method. "historical" uses empirical return distribution, "parametric" assumes normality, "cornish_fisher" adjusts for skew and kurtosis. Default: "historical".historical
benchmarkNoBenchmark ticker for beta calculation, e.g. SPY or QQQ. Default: SPY.SPY
lookback_daysNoNumber of historical trading days to use. 252 ≈ 1 year, 756 ≈ 3 years. Range: 30-1260. Default: 252.
Behavior2/5

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

With no annotations, the description fails to disclose behavioral traits such as data fetching, rate limits, or side effects; it only lists metrics without describing what the tool actually does beyond calculation.

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

Conciseness4/5

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

The description is a single, clear sentence that is efficient, but could be structured with bullet points for better readability.

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

Completeness2/5

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

The description lacks detail on return values or overall behavior; given the complexity and absence of output schema, more context about what the tool returns is needed.

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?

The input schema provides thorough descriptions for all 6 parameters, so the description adds no additional meaning; baseline score of 3 is appropriate.

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?

The description explicitly states the tool calculates core risk metrics (VaR, CVaR, volatility, beta, max drawdown) for a portfolio, which is specific and sets it apart from siblings like stress_test or monte_carlo_simulation.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives; no prerequisites, exclusions, or context about when the tool is appropriate is provided.

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

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