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Glama

calibrate_swaption_model

Calibrate a Hull-White model to swaption volatilities, returning fitted parameters, RMSE, and helper count for pricing and risk analysis.

Instructions

Calibrate a Hull-White model to swaption vols (POST /calibrate-swaption-model) from a raw CalibrateSwaptionModelRequest body (pricing with a SwaptionModelSpec in Calibrate mode and its hw_calibration block, model_id). Validated, then forwarded; see the hwcal_* examples. summary: hw_a, hw_sigma, rmse, num_helpers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
request_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description must carry the full behavioral burden. It discloses only that the body is 'validated, then forwarded', which is a minor processing detail, but says nothing about permissions, cost, rate limits, or side effects of a calibration job.

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

Conciseness3/5

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

The sentence is front-loaded with the action and endpoint, which is good. However, it is dense with backtick-laden jargon, and the trailing summary-field list (hw_a, hw_sigma, rmse, num_helpers) is largely redundant given an output schema exists.

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

Completeness3/5

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

An output schema exists, so the return-value listing is unnecessary duplication. For a nested 0%-covered body, the description gives a reasonable structural sketch and points at examples, but an agent still lacks the concrete shape of the required body to invoke it confidently.

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 0% on a nested body object, so the description has to compensate. It partially does by naming the body contents ('pricing' with a SwaptionModelSpec in Calibrate mode, its 'hw_calibration' block, and 'model_id'), but it leaves request_id undocumented and the construction details deferred to external examples.

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 states a specific verb+resource: calibrating a Hull-White model to swaption vols, and pins it to the POST /calibrate-swaption-model endpoint. It is mostly distinguishable from siblings, though it never explicitly contrasts itself with calibrate_swaption_vol, which an agent could easily confuse it with.

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 alternatives such as calibrate_swaption_vol or price_swaption. The only routing hint is 'see the hwcal_* examples', which requires the agent to go look up another resource rather than deciding from the description.

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