Skip to main content
Glama

calculators

Body Fat Percentage Calculator (Navy Method)

body_fat_calculator

Body Fat Percentage Calculator (Navy Method) — Estimate your body fat percentage with the US Navy tape-measure method. Enter your sex, height, neck, waist, and hip to see body fat and lean body mass.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sexYes
hipCmNo
neckCmYes
waistCmYes
heightCmYes
weightKgNo

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It communicates this is an estimation/calculation tool and names the outputs (body fat and lean body mass). However, it does not disclose method limitations, accuracy caveats, or that hip measurement is only required for females, which is a notable behavioral nuance.

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?

Two sentences, front-loaded with the method name and primary purpose. Every phrase adds value: method, what it estimates, inputs, and outputs. No wasted words or redundancy.

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?

For a calculator with no annotations and no output schema, the description covers the core purpose, inputs, and outputs. However, the female-only hip requirement and the use of centimeters (implied only by schema property names) are missing, which are important contextual details for correct use.

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?

With 0% schema description coverage, the description compensates by enumerating most parameters in plain English (sex, height, neck, waist, hip). It fails to explain the hipCm parameter is conditional on sex and omits weightKg entirely, which leaves a partial gap in parameter understanding.

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 clearly states the tool estimates body fat percentage using the US Navy tape-measure method, with a specific verb ('Estimate') and resource ('body fat percentage'). This distinguishes it from sibling calculators like ideal_weight_calculator or tdee_calculator, which target different health metrics.

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?

The description clearly conveys when to use the tool (when body fat percentage is needed via the Navy method) and lists the required inputs. It does not explicitly exclude alternatives, but the method name and input list provide enough context for a knowledgeable agent to select it over sibling calculators.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.1/5.0
Disambiguation2/5

Many calculators occupy overlapping conceptual spaces, such as 'ai_roi_calculator' vs 'ai_automation_payback_calculator' and 'llm_self_host_vs_api_calculator' vs 'ai_build_vs_buy_calculator'. The boundaries between debt payoff, savings goal, and drawdown tools are also fuzzy, making it easy for an agent to select the wrong tool despite detailed descriptions.

Naming Consistency5/5

Every tool follows the same <topic>_calculator pattern with lowercase snake_case, making the naming highly predictable and consistent. Even acronyms and numbers fit the pattern, so there is no mixing of conventions.

Tool Count1/5

122 tools is an extreme number for a single MCP server, far exceeding the 50+ threshold for a severe mismatch. The tools span unrelated domains like AI costs, pet food, concrete, pizza dough, and turkey cooking, creating an unfocused kitchen-sink surface that overwhelms an agent's selection process.

Completeness3/5

The set covers many common calculator categories such as finance, construction, health, and AI costs, but several staple calculators are missing (e.g., BMI, tip, discount, simple interest, currency conversion). The AI cost cluster is over-saturated while other everyday calculations are absent, leaving minor but noticeable gaps.

Resources