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Run a calculator

run_calculator
Read-onlyIdempotent

Run one calculator (ids from list_calculators) with explicit inputs and return the answer with worked steps. Field types: number (JSON number, or a string such as '2,5' or '-3'), fraction ({"n":3,"d":4} or '3/4'), list (array of numbers or '4; 7; 9'), text (a formula string such as 'x^3 - 2x'). Calculators with units accept inputs.unit (e.g. 'cm').

Input Schema

NameRequiredDescriptionDefault
modeNoMode id of that calculator (see list_calculators). Defaults to the first mode.
inputsYesField id → value.
languageNoLanguage of the steps: nl (Dutch, default) or en (English).nl
calculatorYesCalculator id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false, and destructiveHint=false. The description adds useful behavioral context beyond annotations: it returns worked steps, accepts unit values via inputs.unit, and defines input value encodings. It does not contradict the annotations.

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

Conciseness5/5

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

The description is a single dense paragraph with the purpose front-loaded, followed by practical input-format examples. Every sentence adds usable information without repetition or filler.

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 tool with nested inputs and no output schema, the description covers the call-critical details: calculator id source, input value formats, unit handling, and the fact that worked steps are returned. A minor gap is that it does not explicitly state where per-calculator field ids and modes are discovered, though list_calculators is implied.

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 coverage is 100%, so the schema documents calculator, mode, inputs, and language. The description adds meaningful semantics beyond the schema for the nested inputs object, explaining how number, fraction, list, text, and unit values should be encoded. It leaves mode and language details to the schema.

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 and resource: run one calculator using an id from list_calculators with explicit inputs, and return the answer with worked steps. It clearly separates this from the listing tool, but does not explicitly differentiate it from the other sibling, solve_math_question.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear usage context: obtain calculator ids from list_calculators and provide explicit inputs. It does not state when not to use this tool or when solve_math_question would be the better alternative.

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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