ml_publicacionRetrieve complete details for a MercadoLibre listing by item ID, including price, stock, sales, type, warranty, shipping, and link for seller account queries.
Detalle completo de una publicación: precio, stock, ventas, tipo, garantía, envío, link.
| Name | Required | Description | Default |
|---|---|---|---|
| cuenta | No | user_id de la cuenta de ML si hay varias conectadas (ver ml_cuentas) | |
| item_id | Yes | ID del ítem, ej: MLA123456789 |
Changes observed during successful MCP inspections.
v1.15.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
readOnlyHint=true already establishes this is a safe read, so the description does not need to restate safety. It does add value by enumerating the returned fields (precio, stock, ventas, garantía, envío, link), which matters because no output schema exists. It omits any note on whether item_id is resolved per marketplace (e.g., MLA prefix) or error behavior for missing items.
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 front-loaded sentence with no filler; the field list is informative rather than padding. Slightly dense with a seven-item enumeration, but every element earns its place given there is no output schema.
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 single-item fetch with two fully documented parameters, the definition covers the essentials, and listing the returned fields partially compensates for the absent output schema. The main remaining gap is routing guidance against ml_publicaciones, which is a usage rather than a completeness issue.
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 description coverage is 100%: item_id is documented with the MLA123456789 example and cuenta is documented with a pointer to ml_cuentas. The description adds no parameter-level meaning beyond this, so the baseline 3 applies.
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 pairs a clear resource (una publicación, singular) with the content it returns (precio, stock, ventas, tipo, garantía, envío, link), so an agent can tell this is a single-item detail fetch. It does not explicitly contrast itself with the sibling ml_publicaciones (plural listing), leaving the singular/plural distinction to inference.
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?
No when-to-use statement, no preconditions, and no mention of alternatives such as ml_publicaciones or ml_actualizar_publicacion. Usage is only implied by the singular resource name, which is minimal guidance for a tool sitting in a cluster of listing-related siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.