Skip to main content
Glama

Estimate body fat without a photo

estimate_body_fat
Read-only

Body fat estimates from published equations using tape measurements: Relative Fat Mass (height, waist), U.S. Navy (adds neck, plus hip for women) and Deurenberg (adds weight, age). For adults and general wellness only, not medical advice. No photo needed.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "height_cm": "<height_cm>",
      "waist_cm": "<waist_cm>",
      "gender": "<gender>"
    },
    "name": "estimate_body_fat"
  }
}

Input Schema

NameRequiredDescriptionDefault
ageNo
genderYes
hip_cmNo
neck_cmNo
waist_cmYes
height_cmYes
weight_kgNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real context beyond that: the estimates come from published equations, the population is adults only, and the output is wellness guidance rather than medical advice. It stops short of saying whether all three estimates are always returned or only those whose inputs were supplied.

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?

Two sentences, front-loaded with the method inventory, with the caveat trailing. Dense but readable; the parenthetical parameter lists are efficient. 'No photo needed' partially echoes the title but earns its place by differentiating from the scan siblings.

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?

There is no output schema and no return-value description, so an agent does not know the response shape (per-method percentages, a single number, or a comparison). It also does not state what happens when optional inputs like age or weight are omitted. For a 7-parameter computation tool with a bare schema, those gaps matter.

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 carries the full burden and does so well: it maps parameters to methods (height+waist for RFM; neck added for Navy, hip additionally for women; weight+age for Deurenberg). It also implicitly explains why gender is an enum requirement and why hip is conditional on gender, which the schema alone does not convey.

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?

States a specific verb and resource ('body fat estimates') and immediately names the three published equations used (Relative Fat Mass, U.S. Navy, Deurenberg). The 'no photo needed' clause separates it from the body-scan siblings, so an agent can route without opening the schema.

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 description sets a scope boundary ('adults and general wellness only, not medical advice') which is useful for eligibility, but it never says when to pick this over get_body_scan_integration or get_body_scan_sample_response. The alternative is only implied by the 'no photo' phrasing, so an agent must infer the routing rule.

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.