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Declan142

calcnook

calculate_bmi_bmr_tdee

Compute BMI with WHO category, BMR via Mifflin-St Jeor, or TDEE from BMR and activity level. Provide weight, height, age, sex, or activity level to obtain results.

Instructions

Health metrics in three modes: (1) bmi — Body Mass Index and WHO category; (2) bmr — Basal Metabolic Rate (Mifflin-St Jeor); (3) tdee — Total Daily Energy Expenditure from BMR and activity level. Example queries: 'BMI for 70kg 175cm', 'BMR for 30-year-old male 80kg 180cm', 'TDEE for moderately active person with BMR 1700'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesWhich health metric to compute.
weight_kgNo[bmi, bmr] Body weight in kilograms.
height_cmNo[bmi, bmr] Height in centimetres.
age_yearsNo[bmr] Age in whole years.
sexNo[bmr] Biological sex for the Mifflin-St Jeor equation.
bmr_kcalNo[tdee] Basal Metabolic Rate in kcal (output of bmr mode).
activity_levelNo[tdee] Activity level: sedentary, light, moderate, active, very_active.
Behavior3/5

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

No annotations are provided, so the description must fully disclose behavior. It states the tool computes metrics using specific formulas (e.g., Mifflin-St Jeor) and mentions WHO categories for BMI. However, it does not detail return format, rounding, or constraints. This is adequate for a straightforward calculator.

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 sentence with embedded examples, making it concise and informative. It front-loads the three modes and uses parentheses to clarify. Every element serves a purpose.

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

Completeness4/5

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

Given the tool has 7 parameters and no output schema, the description explains the three modes and their associated outputs (BMI category, BMR value, TDEE from BMR+activity). It covers the essential context for an agent to select and invoke the correct mode.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the bar is lower. The description adds value by grouping parameters by mode (e.g., [bmi, bmr] for weight_kg) and providing example queries that illustrate parameter usage. This exceeds what the schema alone offers.

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 specifies the tool computes three distinct health metrics (bmi, bmr, tdee) using named formulas (Mifflin-St Jeor) and provides example queries. This clearly distinguishes it from sibling calculator tools.

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 lists the three modes and gives example queries for each, making it clear when to use each mode. It does not explicitly state when not to use or compare to alternatives, but the mode separation is intuitive.

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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