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Simular cambio de precios

ml_simular_precios
Read-only

Simulate configured price rules (percentage or fixed amount) on your catalog to preview new prices and deltas per listing without altering MercadoLibre.

Instructions

Aplica las reglas de precio configuradas (porcentaje o monto fijo) sobre el catálogo y devuelve el precio nuevo y el delta de cada publicación, SIN tocar nada en MercadoLibre. Es una simulación.

Input Schema

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

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the non-mutating behavior is partially covered there. The description adds useful behavioral detail by stating that configured rules (percentage or fixed amount) are applied and that non-persistent results are returned, without contradicting the annotations.

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, compact sentence packs the action, the rule types, the output, and the crucial non-mutating guarantee. There is no filler, and the most important differentiator—simulation, no changes to MercadoLibre—is clearly emphasized.

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?

For a tool with no output schema, the description does a decent job explaining the return values (new price and delta) and the non-mutating nature. However, it omits any explanation of how 'limite' behaves and does not describe the output structure beyond a brief phrase, leaving some gaps for correct invocation and result interpretation.

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

Parameters2/5

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

Schema description coverage is only 50%: 'cuenta' has a description but 'limite' does not. The description adds no parameter-level meaning and does not mention that 'limite' constrains the simulation size or that 'cuenta' selects the target account. It fails to compensate for the schema's missing parameter documentation.

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 names a specific action—apply configured price rules—and a specific resource, the catalog, then states exactly what it returns: new price and delta per publication. The emphatic 'SIN tocar nada en MercadoLibre. Es una simulación.' clearly distinguishes this from real price-change operations among siblings.

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 makes the usage context explicit: use this when you want to preview price changes without affecting MercadoLibre. It clearly signals a simulation use case, though it does not explicitly name an alternative like ml_cambios_precio or state when that alternative should be used instead.

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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