get_listing_quality

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

No annotations exist, so the description must disclose behavioral traits. It indicates a read operation but fails to clarify scope (e.g., whether it returns data for all ASINs or requires an ASIN ID, despite no parameters). No mention of rate limits, pagination, or other side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that concisely conveys purpose and content. Every word earns its place without redundancy.

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

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

Given no output schema, the description partially explains return values by listing data points, but it lacks detail on output structure (e.g., whether returned per ASIN, format). The tool is simple, so the gap is moderate.

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

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

The input schema has zero parameters, and schema description coverage is 100%. Per guidelines, 0 parameters gives a baseline of 4. The description adds no parameter semantics but doesn't need to since there are none.

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

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

The description clearly states the tool reads listing quality scoring and enumerates specific aspects (title length, bullet completeness, etc.). It uses a specific verb ('Read') and resource ('listing quality scoring'), and the listed aspects distinguish it from sibling tools like get_product_details.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies this tool is used to retrieve listing quality data, but it does not specify when to use it vs. alternatives or provide any context about prerequisites or exclusions. No guidance on when not to use is given.

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