datalab_shopping_keyword_by_gender

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

No annotations are provided, so the description carries the full burden. It states the tool analyzes gender click ratios but gives no additional behavioral information such as return format, required permissions, or data limitations. This is a minimal restatement of purpose with no extra transparency.

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, focused sentence in Korean, front-loading the tool's purpose without wasting words. It earns its place with specific terminology.

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?

Without an output schema, the description should clarify what results the agent will receive, such as percentage breakdowns or time series. It only states the analysis goal, leaving the response structure unspecified. This is insufficient for a tool with six parameters and no output schema.

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?

Schema descriptions cover 67% of parameters (startDate, endDate, keyword, category) with enums for timeUnit and device. The description adds context that the keyword is for a specific category and that the analysis is gender-based, but does not explain individual parameters beyond the schema. It adds moderate value but doesn't compensate fully for the missing timeUnit/device descriptions.

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 analyzes Naver shopping keyword gender click ratios, using the Korean verb '분석합니다' (analyzes). It distinguishes from sibling tools by specifying '성별' (gender), differentiating it from age/device variants.

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 provides clear context that this is for gender-specific analysis but does not explicitly name alternative tools or state when not to use it. It implies the use case (comparing male vs. female clicks) but lacks exclusionary guidance.

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