search_seoul_datasets

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

No annotations are provided, so the description carries the behavioral disclosure burden. It discloses that the tool performs a direct search and returns raw results plus totalMatchCount, which is useful, but it does not mention result ordering, pagination semantics, or output structure.

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, tight sentence that front-loads the core action and return value. Every phrase earns its place with no filler.

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?

All parameters are described in the schema, and the description explains the key return field totalMatchCount, so invocation is feasible. However, with no output schema, '원시 검색 결과' is underspecified and the exact result shape is not disclosed, making this minimally complete rather than fully complete.

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 description coverage is 100%, so the schema already documents all five parameters. The description adds minimal parameter-level value beyond reinforcing the keyword concept and the service-name criterion.

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 states a specific verb ('검색합니다'), a specific resource ('서울 열린데이터광장 카탈로그'), and a clear scope ('서비스명 기준'). It also clarifies this is a direct keyword search and what it returns, clearly distinguishing it from the sibling recommendation, detail, refine, and recent-list tools.

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 the appropriate usage: use this when you want a direct keyword search of the catalog. However, it does not explicitly state when to use this tool versus alternatives such as recommend_seoul_apis_for_idea or refine_seoul_recommendations, leaving routing to inference.

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