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calendar_advance

Advance a date by a specified tenor on QuantLib calendars, applying business-day conventions, end-of-month rules, and holiday overrides to return the adjusted date.

Instructions

Advance a date by a tenor on a QuantLib calendar (POST /calendar-advance).

Args: calendar: engine Calendar enum value. date: YYYY-MM-DD start date. tenor_number: number of units; negative shifts backwards. tenor_unit: engine TimeUnit (Days, Weeks, Months, Years, ...). convention: engine BusinessDayConvention (Following, ModifiedFollowing, Preceding, Unadjusted, ...). end_of_month: apply the end-of-month rule (default False). calendar_overrides: optional per-request holiday corrections.

summary = {input_date, advanced_date} taken from the engine's response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYes
calendarYes
conventionYes
tenor_unitYes
end_of_monthNo
tenor_numberYes
calendar_overridesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.4

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully states that negative tenor_number shifts backwards, that end_of_month defaults to False, that calendar_overrides are per-request, and it gives the return shape. However, it does not cover error behavior, side effects, or whether the operation is purely computational.

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 definition is well-structured, with a concise purpose line followed by an Args list. It is slightly redundant in restating the return summary even though an output schema exists, but the structure is front-loaded and readable.

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?

For a 7-parameter calculation endpoint with no annotations and an existing output schema, the description is largely complete: it documents every parameter and confirms the return object. The main gap is the absence of usage guidance relative to sibling calendar tools.

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?

Schema description coverage is 0%, so the description must compensate, and it does: every top-level parameter is described with format, meaning, and defaults. Notable details include YYYY-MM-DD date format, negative tenor semantics, enum references for calendar/tenor_unit/convention, and the default for end_of_month.

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 states a specific verb and resource: 'Advance a date by a tenor on a QuantLib calendar'. This clearly distinguishes it from sibling tools such as calendar_holidays or calendar_business_days, and the HTTP endpoint reinforces its narrow scope.

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 explains what the tool does but gives no explicit guidance on when to use it versus alternatives. There is no mention of prerequisites, when-not-to-use, or sibling tools like calendar_business_days.

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