ml_comisionesCalculates MercadoLibre Colombia selling fees for a given price and listing type to help sellers estimate margins.
Cuánto cobra MercadoLibre por vender a un precio dado (comisión por tipo de publicación), para calcular márgenes.
| Name | Required | Description | Default |
|---|---|---|---|
| sitio | No | ||
| cuenta | No | user_id de la cuenta de ML si hay varias conectadas (ver ml_cuentas) | |
| precio | Yes | ||
| categoria | No | ID de categoría, ej MCO1055 |
Changes observed during successful MCP inspections.
v1.30.0-tyl.1Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
readOnlyHint=true already covers the safety profile, so the description only needs added context, and it does add one useful fact: the fee varies by tipo de publicación. However, it doesn't say whether multiple connected accounts or sites affect the result, nor what the return looks like (a single fee or a breakdown).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single compact sentence with the core action front-loaded and no filler. It is appropriately sized, though the mention of listing type without a matching parameter costs it a point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only calculator with no output schema, the description should signal what comes back (fee amount, breakdown by listing type/installments). That return shape is only gestured at, but the core semantics needed to call it are present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 50% (sitio and precio are undocumented), so the description should compensate, but it only echoes 'precio dado' and mentions 'tipo de publicación' — a dimension that has no corresponding parameter in the schema, which can mislead an agent. It adds no meaning for sitio or categoria beyond what the schema already says.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific action and resource: computing what MercadoLibre charges in fees for a given sale price, broken down by listing type, for margin calculation. Clear enough to distinguish from generic sales tools, though it doesn't explicitly contrast with the closest sibling, ml_rentabilidad, which also deals with margins.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'para calcular márgenes' implies the use case (cost side of a margin calculation) but gives no explicit when-to-use/when-not guidance and never names alternatives like ml_rentabilidad or ml_precio_catalogo. The agent must infer the routing decision from tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.