datalab_search

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

No annotations are present, so the description carries the full burden for behavioral disclosure. Yet it only states the action ('trend analysis') without mentioning expected output, read-only nature, rate limits, or any operational constraints, leaving significant ambiguity for the agent.

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 sentence, front-loads the primary verb, and contains no filler. It is concise and easy to parse, though it sacrifices informative content for brevity.

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?

With four required parameters and no output schema, the description is under-specified. It does not explain the return value structure, how results are grouped by timeUnit, or any practical use cases, leaving the agent with significant gaps in understanding.

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 100% coverage with descriptions for all four parameters (startDate, endDate, timeUnit, keywordGroups), so the schema already defines their meaning. The description adds no extra parameter context, but the baseline of 3 is appropriate given the schema completeness.

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 names a clear verb ('Perform') and resource ('trend analysis on Naver search keywords'), which correctly distinguishes it from search_* and datalab_shopping_* sibling tools. However, it doesn't specify the nature of the trend (e.g., search volume over time), so it stops short of being fully specific.

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 no when-to-use guidance or alternative recommendations. It fails to explain how datalab_search differs from the numerous sibling tools or under what circumstances it should be preferred.

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