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Glama

bootstrap_inflation_curve

Build inflation curves from market data by validating and sending a request to the QuantLib pricing engine; returns the constructed curve and exact request.

Instructions

POST /bootstrap-inflation-curves with a raw request body (validated first).

Args: body: the engine's BootstrapInflationCurvesRequest (see engine_schema('/bootstrap-inflation-curves')); no preset support yet, the body is sent as given once it validates. request_id: optional X-Request-Id.

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

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses that the body is validated first, sent as given once validated, and that preset support is absent, but it omits auth requirements, side effects, error behavior, and response handling.

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 front-loaded with the endpoint and validation behavior, then lists Args efficiently. It is appropriately sized with little waste, though the docstring formatting is slightly mechanical.

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 return values need not be explained. The description covers parameters and validation, but for a raw engine endpoint it does not explain when to use this over close siblings such as engine_request or bootstrap_curve, leaving a gap in selection context.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It documents both parameters: body is the raw engine BootstrapInflationCurvesRequest (with a pointer to engine_schema for its shape) and request_id maps to the optional X-Request-Id header.

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 action and resource: POST /bootstrap-inflation-curves with a raw body. It is clear what the tool does, but it does not differentiate from siblings like bootstrap_curve or engine_request, so it falls short of a 5.

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?

The description gives no explicit when-to-use guidance or alternatives. It only notes that presets are not yet supported and points to engine_schema for the body schema, leaving the agent to infer when this tool is preferable to other curve-building or generic request tools.

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