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ncosic

Webotee Amazon Product Research

top_expanding_operators

Read-only

Identify sellers expanding into new brands within a recent time window. Filter by minimum new brands, marketplace, and other criteria.

Instructions

Find sellers (operators) expanding into the most NEW brands in a recent window. Use when the user asks 'operators expanding into new brands', 'sellers growing fastest by brand count', 'who is moving into new brands this month', or any cross-cutting operator question without a specific seller named.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
window_daysNoDays back for 'new' brands (default 30, max 90).
min_new_brandsNoMinimum new-brand count to surface (default 3).
limitNo
marketplace_idNo1 = Amazon UK, 2 = Amazon US (default)
seller_nameNoExact seller/operator name (case-insensitive).
seller_name_containsNo
max_new_brands_in_windowNo
min_total_brandsNo
max_total_brandsNo
min_total_asinsNo
max_total_asinsNo
min_total_observed_buybox_daysNo
max_total_observed_buybox_daysNo
min_operator_fba_share_pctNo
max_operator_fba_share_pctNo
min_avg_ratingNo
max_avg_ratingNo
min_avg_rating_countNo
max_avg_rating_countNo
Behavior3/5

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

The readOnlyHint annotation already indicates a read-only operation. The description adds no further behavioral details like rate limits, authorization, or output behavior, which is adequate but not excellent.

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?

The description is extremely concise: one sentence plus usage examples. Every sentence serves a purpose, front-loaded with the core action.

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

Completeness2/5

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

Given the high parameter count (19), no output schema, and low schema coverage, the description is too brief. It does not explain output order, pagination, or filter interactions, leaving the agent underinformed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With only 21% schema coverage, many parameters lack descriptions. The tool description does not elaborate on any parameter, relying solely on the sparse schema. This fails to add meaning beyond the schema for most parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool finds sellers expanding into new brands, with specific verb and resource. It provides example queries distinguishing it from sibling tools like operator_new_brands and brands_gaining_sellers.

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?

The description explicitly says 'Use when the user asks...' with multiple examples and clarifies it's for cross-cutting queries without a specific seller. Lacks explicit when-not-to-use but provides strong usage context.

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

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