datalab_shopping_keywords

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

With no annotations provided, the description carries the full burden but only says 'Perform a trend analysis.' It does not disclose the return format, pagination, rate limits, or any operational constraints. The term 'analysis' implies read-only, but that is not explicit, and no behavioral details are given.

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 directly states the action and resource. The Korean translation is a minor addition that does not inflate the content. There is no superfluous wording.

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?

This is a moderately complex tool with 5 required parameters, no output schema, and no annotations. The description fails to explain what the trend analysis returns or how parameters interact, leaving significant gaps for an agent to correctly invoke the tool.

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 provides full descriptions for all 5 parameters (100% coverage), so the baseline of 3 applies. The description adds no extra meaning beyond what the schema already documents; it merely states the overall purpose.

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 performs trend analysis on Naver Shopping keywords, using a specific verb ('Perform') and resource ('Naver Shopping keywords'). This distinguishes it from sibling tools that break down by device, gender, or age, making the purpose unambiguous.

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?

No guidance is provided on when to use this tool versus the numerous sibling tools (e.g., datalab_shopping_keyword_by_device). The description does not mention alternatives, exclusions, or context for when the general keyword trend tool is appropriate.

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