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Convert a size

convert_size
Read-onlyIdempotent

Converts one shoe size of a brand between the EU, US and UK systems using the brand's own size chart.

Input Schema

NameRequiredDescriptionDefault
brandYesThe brand, for example 'nike', 'adidas' or 'new balance'.
valueYesThe size in from_system, for example '42', '42.5' or '9'.
to_systemYes
from_systemYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely useful context that results are brand-specific because the brand's own chart is used, but says nothing about failure behavior for unknown brands/sizes or what the returned value looks like.

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?

A single front-loaded sentence with no filler; every clause (single size, brand-specific, three systems) carries information the agent needs.

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?

The tool is simple and read-only, and the description covers the input semantics adequately. However, with no output schema, the description should indicate what is returned (e.g. a size string in the target system, or an error when the brand has no matching chart) and it does not.

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?

With 50% schema coverage, the two undocumented params (from_system, to_system) are enums whose meaning is made explicit by the description naming the EU, US and UK systems. It also clarifies that only one size value is converted and that brand selects the chart, adding meaning beyond the schema's example values.

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?

States a specific verb and resource — converting a single shoe size between EU/US/UK using a brand's own chart. It is unambiguous and clearly distinct from siblings like search_sneakers or get_offers, though it doesn't explicitly name those alternatives.

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 context of use is implied by the verb 'converts' and the size-system scope, so an agent can infer when to reach for it. There is no explicit statement of when not to use it, no prerequisites (e.g. unknown brand handling), and no reference to alternatives.

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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