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Costos por publicación

ml_costos_publicaciones
Read-only

Calculate MercadoLibre commission and shipping fees per category to determine net revenue before setting your price.

Instructions

Comisión y costo de envío que cobra MercadoLibre por cada publicación, agrupado por categoría. Sirve para saber cuánto se lleva ML de cada venta antes de fijar precio.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cuentaNoID de la cuenta de MercadoLibre. Omitir para la cuenta por defecto.
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so no contradiction exists. The description adds useful behavioral context by specifying that data is grouped by category and represents the commission and shipping cost per publication. It does not detail data freshness or whether values are percentages, but given the annotation coverage, this is acceptable.

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?

Two concise sentences: the first states what the tool returns, and the second states its purpose. No filler or repetition. The description is efficiently front-loaded with the core resource and grouping information.

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?

For a simple read-only tool with one optional parameter and no output schema, the description adequately communicates the output shape ('agrupado por categoría') and the practical use case. Minor omissions like currency or whether the fee is a percentage are not severe for selecting and invoking the 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?

The schema has 100% coverage: the only parameter, 'cuenta', is fully described as 'ID de la cuenta de MercadoLibre. Omitir para la cuenta por defecto.' The description itself does not add any information about the parameter, so the baseline score of 3 applies.

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?

The description clearly identifies the resource: commissions and shipping costs charged by MercadoLibre per publication, grouped by category. It also gives the intended use case ('saber cuánto se lleva ML de cada venta antes de fijar precio'). However, it lacks an explicit verb like 'obtener' or 'consultar', so it is a noun-phrase description rather than a full imperative statement, and it does not explicitly distinguish itself from sibling 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 gives a clear context for when to use the tool: before setting a price, to know how much MercadoLibre takes from each sale. It does not mention alternatives or explicitly state when not to use it, but the use case is specific enough to guide an agent.

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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