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ncosic

Webotee Amazon Product Research

operator_category_dominance

Read-only

Show which product categories an operator dominates by brand count and observed buybox days.

Instructions

Show which product categories an operator dominates. Returns categories ranked by the operator's brand count and observed buybox days in each. Use when the user asks 'what categories does this seller focus on', 'operator category breakdown', 'where does Amazon Warehouse dominate', or any category-scoped operator question.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operator_nameYesSeller/operator name.
marketplace_idNo1 = Amazon UK, 2 = Amazon US (default)
limitNo
category_nameNoExact category name (case-insensitive).
category_name_containsNo
min_brand_countNo
max_brand_countNo
min_total_asinsNo
max_total_asinsNo
min_total_observed_buybox_daysNo
max_total_observed_buybox_daysNo
Behavior3/5

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

Annotations already declare readOnlyHint=true. The description adds that results are ranked by brand count and buybox days, which is helpful. No additional behavioral traits (e.g., rate limits, data freshness) are disclosed. No contradiction with annotations.

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?

The description is concise with two sentences plus query examples. It front-loads the core purpose. However, it could be slightly more structured (e.g., bullet points for parameters).

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?

No output schema is provided, but the description explains the return structure (categories ranked by metrics). With 11 parameters, low schema coverage, and no output schema, the description is moderately complete but not fully comprehensive.

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?

Schema description coverage is low at 27%. The description mentions key metrics but does not explain the meaning of many parameters (e.g., limit, category_name_contains, min/max fields). It adds minimal value beyond the parameter names and brief schema descriptions.

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 clearly states the tool shows categories dominated by an operator, ranked by brand count and buybox days. Example queries are provided. However, it does not explicitly differentiate from similar sibling tools like 'operator_top_brands' or 'operator_brands_by_competition'.

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?

The description gives explicit usage examples and query patterns, but lacks guidance on when not to use this tool or mentions of alternative tools for related questions.

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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