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smartscout_brand_search

Search for brands and retrieve their revenue, growth, and product metrics to identify Amazon market opportunities.

Instructions

Search for brands and get their performance metrics

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brandNoBrand name to search for (partial match)
limitNoNumber of results
orderByNoColumn to order byREVENUE
minRevenueNoMinimum monthly revenue
minGrowth30NoMinimum 30-day revenue growth percentage
minProductsNoMinimum number of products

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It doesn't state that this is a read-only operation, whether results are paginated, what metric fields are returned, or any auth/rate-limit constraints. 'Get their performance metrics' is the only behavioral hint and is too vague to act on.

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?

A single efficient sentence with no filler, and the core action is front-loaded. It is appropriately sized but arguably too terse for a six-parameter tool, which slightly undercuts the value of the brevity.

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 no output schema, the description should clarify what 'performance metrics' means (revenue, growth, ratings) since it is the only source for that. Combined with the absence of annotations and any usage context, the definition is minimally viable but leaves real gaps for a tool with six optional filters.

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 (brand, limit, orderBy, minRevenue, minGrowth30, minProducts) are already documented in the schema, including the orderBy enum and defaults. The description adds nothing beyond that, so baseline 3 applies.

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 (search) and resource (brands) plus what comes back (performance metrics), which is clearer than a bare 'search' tool. However, it does not differentiate from the many sibling brand tools (brand_details, brand_coverage, brand_growth), leaving the agent to guess which brand tool to pick.

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

Usage Guidelines2/5

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

No when-to-use guidance, no prerequisites, and no mention of alternatives such as brand_details or brand_growth despite a crowded sibling set. The agent must infer the appropriate context entirely from the name.

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