Skip to main content
Glama
eyetoolkit

mquickcalc-health

by eyetoolkit

body_fat_calculator

Calculate body fat percentage using the US Navy method from waist, neck, height, and hip measurements, with lean body mass output.

Instructions

Body fat % via US Navy Method (waist + neck + height ± hip for females). Also returns lean body mass.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ageYes
sexYes
hipCmNo
neckCmYes
waistCmYes
heightCmYes
weightKgYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It discloses the formula inputs and the additional return value, which is useful, but it does not explain sex-specific input requirements, limitations of the Navy method, or that this is a stateless read-only calculation.

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 a single compact sentence that leads with the main output and method, then adds the secondary output. The '±' shorthand is terse but understandable; no filler is present.

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

Completeness2/5

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

For a tool with 7 parameters and no output schema or annotations, this description is incomplete. It does not clarify that hip is required for females despite being optional in the schema, explain why age and weight are needed, or describe the output format/units of lean body mass.

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

Parameters2/5

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 maps waist, neck, height, and hip to the formula and hints that hip applies only to females, but it does not explain the roles of weight and age, and it omits any statement about units or hip handling despite hip being non-required in 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 identifies the tool's output (body fat percentage) and the specific calculation method (US Navy), plus the secondary output (lean body mass). It is not a tautology and clearly separates this from sibling calculators like BMI or BMR, though it lacks an explicit verb.

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

Usage Guidelines3/5

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

The intended use is implied by the name and description: call it when body fat percentage or lean body mass is requested. However, there is no explicit statement of when to choose it over sibling calculators or any exclusions, so the guidance is indirect.

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