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tresor4k

macalc

calculate_clothing_size_convert

Convert clothing sizes between EU, US, and UK systems for shirts, pants, and dresses, for male or female. Input a size number and source system to get equivalent sizes.

Instructions

Convert clothing size between EU, US and UK systems. Returns: {original}. See list_bundles for related 'conversions' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeYesSize number in source system
from_systemYesSource system
garmentYesType of garment
sexYesSex

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.
Behavior2/5

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

No annotations provided, and the description fails to disclose conversion behavior, error handling, or output structure. 'Returns: {original}' is vague and unhelpful.

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?

Extremely concise with two sentences, no wasted words. Front-loaded with purpose.

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

Completeness2/5

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

Despite having an output schema (context signal), the description offers no hint about the response format or what the conversion yields. Incomplete for a 4-param 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 covers 100% of parameters with clear descriptions and enums, so description adds no extra value. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states conversion between EU, US, and UK systems, distinguishing it from other size converters like shoe or bra size. However, the 'Returns: {original}' placeholder is unclear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to choose this tool over siblings. Only a vague reference to 'list_bundles' for related calculators, missing direct context.

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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