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ncosic

Webotee Amazon Product Research

find_brands_with_high_seller_churn

Read-only

Find brands losing sellers faster than their category average. Set a minimum churn threshold to detect seller instability and potential brand risk.

Instructions

Find brands experiencing high seller churn relative to their category. Returns brands where seller_churn_30d_delta_vs_cat_pp >= the specified threshold (default 5pp). Optionally filtered by category. Use when the user asks about 'brands losing sellers', 'high churn brands', or 'seller instability'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoCategory root name to filter (optional).
min_delta_ppNoMin delta vs category in percentage points. Default 5.
max_delta_ppNoMax delta vs category in percentage points. Omit for no ceiling.
limitNoMax results (capped at 10). Default 10.
marketplace_idNo1 = Amazon UK, 2 = Amazon US (default)
scopeNotracked = only brands on the user's watchlist; universe = all brands. Default universe.
brandNoExact brand match (case-insensitive).
brand_containsNo
min_seller_churn_30d_pctNo
max_seller_churn_30d_pctNo
min_brand_velocity_90d_units_dayNo
max_brand_velocity_90d_units_dayNo
dominant_category_velocity_tier_inNoComma-separated velocity tiers to keep.
Behavior3/5

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

Annotations already declare readOnlyHint=true. The description adds context about the filtering logic (delta vs category, default threshold) which is helpful but not extensive. No contradictions.

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?

Three sentences, front-loaded with purpose, no redundant information. Every sentence adds value.

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?

Core purpose and metric are clear, but the tool has 13 parameters and no output schema. The description does not explain the shape of the results or how the multiple optional filters interact, leaving some ambiguity for complete usage.

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 62%, between the 50-80% range. The description only explains two parameters (min_delta_pp and category) implicitly, leaving many others (e.g., scope, marketplace, brand filters) unexplained. It does not adequately compensate for undocumented parameters.

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?

Description clearly states the tool finds brands with high seller churn relative to category, specifying the metric and threshold. It uses a specific verb ('find') and resource ('brands'), but does not explicitly distinguish from siblings like '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?

Description provides explicit usage hints ('Use when the user asks about...') that guide typical queries. However, it does not mention when not to use the tool or suggest alternatives from the sibling list.

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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