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ncosic

Webotee Amazon Product Research

map_violations_today

Read-only

Identify products with Minimum Advertised Price violations. Filter by brand, retailer, price, or violation percentage to enforce MAP policies.

Instructions

Show active MAP (Minimum Advertised Price) violations for products in the workspace. Use when the user asks 'MAP violations', 'who is selling below MAP', 'price violations today', 'are there any MAP breaches', or any MAP-enforcement question.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brandNoFilter to a specific brand. Omit for all workspace brands.
min_violation_pctNoMinimum violation percentage below MAP (default 0, meaning any violation).
limitNo
max_violation_pctNoMaximum violation percentage below MAP.
brand_containsNoSubstring match on brand (use `brand` for an exact match).
product_title_containsNo
retailer_domainNoExact retailer domain (case-insensitive).
retailer_domain_containsNo
retailer_nameNoExact retailer name (case-insensitive).
retailer_name_containsNo
min_observed_price_usdNo
max_observed_price_usdNo
min_map_floor_usdNo
max_map_floor_usdNo
first_seen_fromNoYYYY-MM-DD.
first_seen_toNo
last_seen_fromNo
last_seen_toNo
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the description correctly implies a read-only operation. However, the description does not add further behavioral context such as what 'active' means, data freshness, pagination, or limits. With annotations covering safety, this is adequate but not enriched.

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 at two sentences, front-loading the core action and following with usage cues. It avoids fluff, though a more structured breakdown (e.g., separating purpose from examples) could improve clarity for agents.

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?

With 18 parameters, no output schema, and no description of return format or behavior, the description is insufficient. It does not explain what 'active' means, whether results are aggregated or per-product, or how violations are calculated. The tool is complex, but the description offers minimal completeness.

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

Parameters1/5

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

The input schema has 18 parameters with only 39% description coverage, yet the tool description adds zero information about any parameter. This is a critical gap; the description must compensate for low schema coverage but fails entirely, leaving agents blind to parameter meaning beyond schema labels.

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 shows 'active MAP violations' with a specific verb ('Show') and resource. It also provides example user queries, making purpose unmistakable and distinct from the long list of sibling tools, none of which focus on MAP violations.

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 lists example queries that trigger this tool ('MAP violations', 'who is selling below MAP', etc.), offering clear context for when to use it. However, it does not mention when not to use it or suggest alternative tools, which would strengthen guidance.

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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