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pedronahum

JACTUS MCP Server

by pedronahum

jactus_compute_risk

Compute financial contract risk metrics (DV01, delta, gamma, PV01) using finite difference approximation on the nominal interest rate. Returns the metric value and base PV.

Instructions

Compute risk metrics (DV01, delta, gamma, PV01) for a contract.

Uses finite difference approximation on the nominal interest rate. Returns the metric value, base PV, and computation parameters.

Args: attributes: Contract attributes dict (same format as simulate). risk_metric: One of "dv01", "delta", "gamma", "pv01". base_rate: Base nominal interest rate (default 0.05). bump_size: Finite difference bump size (default 0.0001 = 1bp).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
base_rateNo
bump_sizeNo
attributesYes
risk_metricNodv01

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Discloses the computational method (finite difference approximation on nominal interest rate) and the return value structure. No annotations exist, so the description carries full burden. It does not explicitly state it is read-only or idempotent, but the method description provides good insight.

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?

Structured with summary, method note, returns line, and parameter list. The Args block is necessary given empty schema descriptions. Could be slightly more concise by merging the method note with the summary, but overall efficient.

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

Completeness4/5

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

Covers method, all parameters, and return values. References 'same format as simulate' for attributes, leveraging existing knowledge. Output schema exists so return details are less critical. Lacks explicit example usage or note about performance/accuracy, but adequate.

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

Parameters5/5

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

The schema has 0% description coverage, so the description fully compensates with an 'Args' block explaining each parameter: attributes (format same as simulate), risk_metric (enumeration of values), base_rate (default 0.05), bump_size (default 1bp). This adds significant meaning beyond the schema.

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?

Clearly states it computes specific risk metrics (DV01, delta, gamma, PV01) for a contract, distinguishing it from sibling tools like simulate_contract which likely compute prices. The verb 'compute' is specific and the resource is 'risk metrics for a contract'.

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 such as simulate_contract or simulate_portfolio. The description does not mention exclusions or contexts where another tool is preferable.

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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