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get_orders

Retrieves a seller's Mercado Libre orders with buyer, item, shipping, and payment details, plus status, date, and pagination filters for sales tracking.

Instructions

Obtiene las órdenes/ventas de un vendedor. Incluye comprador, items, envío y pagos.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "seller_id": "<seller_id>"
    },
    "name": "get_orders"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoCantidad máxima de órdenes (default 20)
offsetNoOffset para paginación
statusNoFiltrar por estado de la orden
date_toNoFecha hasta (ISO 8601)
date_fromNoFecha desde (ISO 8601, ej: 2026-03-01T00:00:00.000-03:00)
seller_idYesID numérico del vendedor en ML

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.0-alpha.3

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full load. The verb "Obtiene" implies a read-only call and the second sentence usefully discloses that responses include buyer, item, shipping and payment sub-objects. It says nothing about authorization needs, default/pagination behavior, or result ordering, leaving real gaps for an unannotated tool.

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 short sentences with zero filler; the core purpose is front-loaded and the return-content note follows naturally. Nothing is repeated from the schema or title.

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?

With six parameters, no annotations and no output schema, the description does partially compensate by naming the response components. Still, it omits pagination semantics (limit default 20, max 50, offset) and the shape of the returned collection, which matter for correct invocation.

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?

Schema description coverage is 100%, so all six parameters (seller_id, limit, offset, status, date_from, date_to) are already documented with types, ranges and the status enum. The description adds no meaning beyond the schema, which is acceptable at the baseline but no better.

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 uses a specific verb and resource ("Obtiene las órdenes/ventas de un vendedor") and even previews the payload (comprador, items, envío, pagos), so the agent knows exactly what entity is being fetched. It does not differentiate itself from sibling tools such as list_products or get_item_metrics, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: an agent can infer this is the tool for pulling a seller's order history, and no sibling in the list competes directly for that job. However, there is no explicit statement of when to use it versus alternatives, no mention of prerequisites (seller_id is required), and no guidance on paging through large result sets.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.