SooTool

medical.bmi

Read-onlyIdempotent

Calculate body mass index from height in meters and weight in kilograms, then classify the result using WHO categories to support health screening.

Instructions

체질량지수(BMI)를 계산하고 WHO 기준으로 분류한다. BMI = weight_kg / height_m^2, 입력은 미터와 킬로그램의 Decimal 문자열, 결과는 소수 2자리 HALF_EVEN 반올림. 분류는 underweight(<18.5), normal(<25), overweight(<30), obese_1(<35), obese_2(<40), obese_3(40 이상)이며 반올림한 값으로 판정한다. 신장을 cm 단위로 넣으면 결과가 100배 이상 어긋난다.

Input Schema

Name	Required	Description	Default
`height_m`	Yes
`weight_kg`	Yes

Output Schema

Name	Required	Description
`bmi`	Yes
`_meta`	No	서버가 붙이는 영수증(integrity), 엔진, 힌트
`trace`	Yes	계산 근거(tool, formula, inputs, steps, output)
`category`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Oct 29, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Beyond the read-only/idempotent annotations, it discloses the exact formula, the rounding mode and precision (HALF_EVEN, 2 decimals), that classification is judged on the rounded value, and a concrete units pitfall (cm input causes 100x error). This is rich, decision-relevant behavioral detail.

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?

Four tightly packed sentences: purpose, formula/input contract, rounding and thresholds, then the units warning front-loaded as the last critical caveat. No filler.

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

Completeness5/5

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

An output schema exists, yet the description still specifies rounding and every classification boundary so the result is interpretable. Input format, units, and failure mode are all covered — nothing an agent needs is missing.

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 must compensate — and it does: it names both parameters via the formula, declares them Decimal strings, fixes units to meters and kilograms, and warns about the cm mistake. An agent has everything needed to pass correct values.

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 ('체질량지수(BMI)를 계산하고') plus the classification scheme applied (WHO). The scope is unambiguous and no sibling tool computes BMI, so differentiation is implicit but perfectly clear.

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 use case is obvious from the tool's name and the description confirms it computes BMI with WHO categories, but it never states when to prefer this over related medical siblings (e.g., medical.bsa) or any preconditions. Adequate implied usage, no explicit when/when-not guidance.

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

Deploy Server