Search the Seoul dataset catalog

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

No annotations are present, so the description carries the transparency burden. It discloses the catalog size, the routing behavior to dedicated tools, and the fallback to call_dataset. This is useful contextual behavior beyond a basic search, though it doesn't specify the response format.

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 compact, but the Korean sentence partly repeats the English sentence. However, it also adds the call_dataset instruction, so each sentence contributes something distinct.

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?

For a simple search tool with one parameter and no output schema, the description provides sufficient context: it names the catalog, explains the routing logic, and points to the alternative for tools without dedicated access. Minor omission is the result format, but not critical.

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 schema covers 100% of the query parameter with a Korean description and examples. The description adds no extra parameter-level detail, so the baseline of 3 applies.

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 it searches a curated catalog of 28 Seoul Open Data datasets by keyword, which is a specific verb-resource pair. It also distinguishes from siblings like search_place and search_cultural_events, which search different types of data.

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?

Explicit guidance is provided: entries with a dedicated tool point you to it, and data without a dedicated tool should be accessed via call_dataset. This clarifies when to use this tool versus the alternatives.

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