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devantage

MCP Calculator

by devantage

unit_conversion

Convert values between units of length, weight, temperature, volume, and area. Specify the value, source unit, target unit, and category to get the converted result.

Instructions

Convert between different units of measurement.

Categories and units — length: mm, cm, m, km, in, ft, yd, mi, mil, μm, nm; weight: mg, g, kg, t, oz, lb, st, ton; temperature: C, F, K, R; volume: ml, cl, dl, l, kl, fl_oz, cup, pt, qt, gal, tsp, tbsp, bbl; area: mm2, cm2, m2, km2, in2, ft2, yd2, mi2, acre, ha.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueYes
to_unitYesTarget unit symbol.
categoryYes
from_unitYesSource unit symbol.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure, but it only lists supported units. It does not mention output format, rounding behavior, unit normalization, temperature conversion specifics, or error handling, leaving important behavioral traits undisclosed.

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 a clear single-sentence purpose followed by a well-organized, categorized list of units. The list is long but necessary for specifying supported values; there is no redundant filler.

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?

The output schema exists and the description provides the category enum and unit lists, so parameter coverage is decent. However, missing usage guidelines and behavioral details (e.g., output structure, temperature conversion behavior) leave the description only minimally complete for a 4-parameter tool.

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?

The schema only describes from_unit and to_unit as 'unit symbol', leaving value and category underdocumented. The description compensates by enumerating valid units per category, which clarifies the allowed parameter values, but it does not explain the value parameter or how category relates to the chosen units.

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 clearly states the tool converts between units of measurement and lists supported categories and units. It is a specific verb+resource statement, but it does not distinguish this tool from the sibling batch_conversion or explain when to use single vs batch conversion.

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 explicit guidance is given on when to use this tool versus alternatives such as batch_conversion. The description only says what the tool does, not the intended use case or exclusions.

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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