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Descubrir nichos (API oficial)

ml_nichos
Read-only

Discovers and validates MercadoLibre niches by analyzing sales rotation, historical demand, competition, and profitability from one search or category; ranks opportunities across multiple keywords.

Instructions

Descubre y valida NICHOS con la API oficial de MercadoLibre (sin Nubimetrics ni planillas). Con UNA búsqueda (o una categoría) da el análisis completo: (1) ordena las publicaciones de mayor a menor ROTACIÓN (unidades por mes = vendidos ÷ antigüedad); (2) si el producto SE VENDE HOY o vendió en el pasado (visitas de los últimos 5 meses contra su promedio histórico); (3) si hay OPORTUNIDAD o MONOPOLIO (cuota del líder, top 3 y HHI entre vendedores); (4) el TECHO DE DEMANDA (unidades por mes del nicho) y cuánto vende hoy alguien que entró en los últimos 90 días; (5) si es TENDENCIA, ESTACIONAL o EVERGREEN; (6) con costo, si los NÚMEROS CIERRAN al precio de mercado (comisión real de ML e impuestos del cerebro). Con VARIAS búsquedas (hasta 5) arma el RANKING DE OPORTUNIDADES con puntaje 0-100. Las ventas de terceros que informa ML pueden ser aproximadas: los resultados son estimaciones sobre una muestra, nunca inventa datos.

Input Schema

NameRequiredDescriptionDefault
costoNoTu costo por unidad (solo con una búsqueda): para ver si los números cierran
sitioNo
cuentaNouser_id de la cuenta de ML si hay varias conectadas (ver ml_cuentas)
muestraNoPublicaciones a analizar por nicho (default 100 con una, 60 con varias; máx 300)
busquedaNoUna keyword, ej "organizador de cocina"
busquedasNoVarias keywords (hasta 5) para el ranking de oportunidades
categoriaNoID de categoría (ej MCO1574) en vez de keyword
costo_envioNoEnvío por unidad a tu cargo (default 0)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.30.0-tyl.1

TDQS

A3.8/5.0
Behavior4/5

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

readOnlyHint=true is consistent with the framing as an analysis/discovery operation. Beyond the annotation it discloses a real behavioral trait: results are estimates over a sample, ML-reported third-party sales may be approximate, and the tool "nunca inventa datos" – material context for trusting the output. It stops short of covering rate limits or latency for a tool that crawls up to 300 listings per niche.

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

Conciseness3/5

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

The core purpose is front-loaded in the first clause, but the six-item numbered enumeration is dense and partly restates what the tool computes in marketing register ("si los NÚMEROS CIERRAN", "impuestos del cerebro"). It is readable but longer than needed to route an agent correctly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an 8-parameter, no-required-parameter analysis tool with no output schema, the description carries the burden of explaining what is returned and does so via the six analysis dimensions plus the 0-100 ranking score. Missing only edge behavior – what happens when neither busqueda, busquedas nor categoria is supplied, and whether error vs empty results differ from low-demand niches.

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?

With 88% schema description coverage the schema already documents busqueda, busquedas, muestra, categoria, costo and cuenta, so the baseline is 3. The description reinforces the exclusivity of busqueda vs busquedas and the costo-with-one-search constraint, but adds no formats, ranges or defaults not already present in 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+resource ("descubre y valida NICHOS") and enumerates the six analyses produced, so an agent knows exactly what comes back. It does not name or distinguish itself from plausible siblings such as ml_descubrir_ganadores, ml_buscar or ml_tendencias, which keeps it from 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 Guidelines4/5

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

Clearly splits the two usage modes – "Con UNA búsqueda (o una categoría)" for a full niche analysis versus "Con VARIAS búsquedas (hasta 5)" for the opportunity ranking – and ties the cost parameter to the single-search mode. It gives no guidance on when to prefer this over the many sibling discovery tools, so no exclusions or alternatives are stated.

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