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shelendrajain2004

Financial Risk MCP Server

calculate_portfolio_greeks

Aggregate Delta, Gamma, Vega, Theta, and Rho across a book of trades to measure portfolio option sensitivities and support risk analysis.

Instructions

Aggregates first- and second-order derivatives sensitivities: Delta, Gamma, Vega, Theta, and Rho across a book of positions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tradesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It implies a computation over positions but says nothing about the pricing model or assumptions, whether results are per-trade or netted, error behavior for malformed trades, or determinism/performance characteristics.

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?

One efficient sentence that front-loads the verb and enumerates the computed sensitivities. It is appropriately short, though the space saved is not used to cover any of the missing behavioral or parameter context.

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?

With no output schema, no annotations, and a complex nested input array at 0% schema coverage, the description should explain the return shape (per-trade vs. portfolio-level Greeks) and pricing assumptions. Neither is present, so an agent cannot confidently predict what it will get back.

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

Parameters2/5

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

Schema description coverage is 0% and the single parameter is a nested array whose fields (trade_id, notional, maturity_years, strike, volatility, option_type, underlying_price) are undocumented. The description adds nothing about required fields, units, or what option_type=LINEAR implies, leaving the caller to guess at the input contract.

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

Purpose4/5

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

The description names a specific verb (aggregates) and resource (Delta, Gamma, Vega, Theta, Rho sensitivities across a book of positions), so the tool's function is unambiguous. However, it offers no differentiation from siblings like compute_portfolio_var or calculate_sacr_exposure, which also operate on a portfolio of positions.

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?

There is no statement of when to use this tool versus the sibling risk tools (VaR, SACR exposure, Monte Carlo PFE), nor any prerequisites such as whether trades must be options or may be linear. The agent must infer usage entirely from the name and the one-sentence purpose.

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