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get_catalog_cleanup

Identify Amazon listings with quality issues that need correction. Filter by date, ASIN, SKU, or marketplace to target specific catalog problems.

Instructions

[Catalog / read] Listings with quality issues to fix. Hosted endpoint only; this local stdio server is an introspection stub.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
start_dateNoOptional start date for time-range reads, YYYY-MM-DD.
end_dateNoOptional end date for time-range reads, YYYY-MM-DD.
asinNoOptional Amazon ASIN filter when relevant.
skuNoOptional merchant SKU filter when relevant.
marketplace_idNoOptional Amazon marketplace identifier.
filtersNoOptional lightweight filters supported by the hosted tool.
limitNoOptional row limit for hosted reads.
Behavior3/5

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

With no annotations, the description partially covers behavior: it states it's a read operation and a stub. However, it does not detail other traits like authentication, rate limits, or what constitutes quality issues, leaving gaps.

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 with two sentences that front-load the purpose and environmental context. No fluff or redundant information.

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?

Despite no output schema, the description lacks detail on return format and what quality issues entail. It is a stub, but as a standalone definition it leaves the agent without enough context to fully understand behavior.

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 coverage is 100% with basic descriptions. The tool description does not add extra meaning beyond the schema, so it meets the baseline but does not compensate for missing detail.

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 reads catalog listings with quality issues, using a specific verb and resource. It distinguishes itself by noting it's a hosted endpoint stub, which separates it from other get_ tools.

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 explains when to use (to list listings with quality issues) but does not provide guidance on when not to use or compare to alternatives. The note about the stub indicates limited functionality but lacks explicit 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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