ml_visitasRetrieves visit counts for a MercadoLibre listing over a configurable day window (default 30) to measure traffic and conversion, with optional account selection for multi-account sellers.
Visitas de una publicación en una ventana de días, para medir tráfico y conversión.
| Name | Required | Description | Default |
|---|---|---|---|
| dias | No | default 30 | |
| cuenta | No | user_id de la cuenta de ML si hay varias conectadas (ver ml_cuentas) | |
| item_id | Yes |
Changes observed during successful MCP inspections.
v1.15.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, confirming a safe read operation. The description adds the temporal window concept and purpose, but it does not disclose rate limits, authentication needs, or return format details beyond what the name implies.
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 sentence that front-loads the resource and purpose with no wasted words. It is appropriately sized for the tool's simplicity.
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 simple read-only metric query, the description covers the basic what and why. But it omits alternative tools (e.g., ml_metricas), does not explain the return shape (no output schema exists), and gives no guidance on the cuenta parameter.
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?
The description indirectly clarifies that item_id refers to a publication and 'ventana de días' maps to the dias parameter. However, it says nothing about the cuenta parameter, and schema coverage is only 67%, leaving one parameter undocumented in the schema.
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?
The description states a specific resource (visits of a publication) and a window of days, making the tool's purpose clear. However, it does not differentiate from similar metric-oriented siblings like ml_metricas or ml_publicacion.
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 medir tráfico y conversión' implies the tool's intended use case, but there is no explicit guidance on when to choose it over alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.