Skip to main content
Glama
mercadolibre-mcp

mercadolibre-mcp

Borrar un clip

ml_borrar_clip

Deletes a clip from a MercadoLibre listing in any moderation state, enabling you to remove rejected clips and upload a corrected version.

Instructions

Borra un clip de una publicación (por ejemplo uno rechazado, para subir la versión corregida). Funciona en cualquier estado de moderación.

Input Schema

NameRequiredDescriptionDefault
cuentaNouser_id de la cuenta de ML si hay varias conectadas (ver ml_cuentas)
item_idYes
clip_uuidYesEl id del clip (sale de ml_clips)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.15.0

TDQS

A3.6/5.0
Behavior3/5

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

readOnlyHint=false already signals a mutating operation. The description usefully adds that the clip can be deleted regardless of moderation state, but says nothing about permanence/irreversibility, whether the clip is recoverable, or permission requirements — meaningful gaps for a delete tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, zero padding, with the action stated first. Efficient and front-loaded, though slightly terse given the destructive nature of the operation.

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 simple delete with a write annotation and no output schema, the description covers scope and use case, but omits consequences of the deletion and the partially-undocumented item_id parameter, leaving an agent with avoidable uncertainty.

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 coverage is 67%: cuenta and clip_uuid are documented in the schema, but item_id is not. The description adds no parameter-level detail (syntax, ids, relationship between item_id and clip_uuid), so it neither compensates for the gap nor goes beyond the schema.

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?

States a specific verb (borra) and resource (un clip de una publicación), plus a concrete use case. It is distinguishable from ml_subir_clip and ml_clips by the deletion semantics, though it never names those siblings explicitly.

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?

Provides a clear when-to-use context ('uno rechazado, para subir la versión corregida') and a scope note ('funciona en cualquier estado de moderación'). No explicit alternatives or exclusion conditions are given, so it falls short of a 5.

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