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tresor4k

macalc

calculate_body_fat

Estimate body fat percentage from BMI, age, and biological sex using the validated Deurenberg equation. Provides body fat percentage for health tracking.

Instructions

Estimate body fat percentage from BMI, age and sex using Deurenberg equation. Returns: {body_fat_pct}. See list_bundles for related 'sante' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bmiYesBody Mass Index
ageYesAge in years
sexYesBiological sex

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoComputed result. Object whose fields depend on the tool (e.g. {tax, marginal_rate, brackets} for tax tools, {volume_l, gallons} for volume tools).
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.
Behavior4/5

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

With no annotations, the description carries full burden. It explains the calculation method (Deurenberg equation), input parameters, and output format. It does not disclose limitations or prerequisites beyond the schema, but for a simple calculator, it is fairly transparent.

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?

The description is two sentences, front-loading the purpose and method. Every sentence provides necessary information without redundancy. It is highly concise and well-structured.

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 presence of an output schema and three straightforward parameters, the description covers purpose, method, and output. It hints at related tools via list_bundles. It could mention validity or the equation's origin, but is largely complete for a calculator tool.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds minimal value by naming parameters in context but does not provide additional semantic details beyond the schema.

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's purpose: estimating body fat percentage from BMI, age, and sex using the Deurenberg equation. It also specifies the return format and distinguishes itself from siblings like calculate_body_fat_navy by naming the specific equation.

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 provides a vague reference to 'list_bundles for related calculators' but does not explicitly state when to use this tool versus alternatives like calculate_body_fat_navy. Usage guidance is implied but not direct.

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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