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

Beyond the read-only and idempotent annotations, it explains parsing behavior: region words are read as administrative areas, abbreviations work, and the rest of the query is matched against record content and dataset names. It also discloses the `interpreted` echo, which is valuable for verifying how the query was understood.

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 English text is front-loaded with the main purpose, examples, parsing behavior, and use case. The Korean translation duplicates the same content without adding new information, slightly padding the description, but the overall length is still compact and scannable.

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 two-parameter tool with no output schema, it covers query format, interpretation behavior, examples, and a way to verify interpretation via `interpreted`. It could briefly describe the shape of returned records, but nothing essential for correct invocation is missing.

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 coverage is 100%, so the baseline is 3, but the description adds meaningful semantic detail for the query parameter: administrative-area interpretation, abbreviation support, and matching targets. It adds nothing about limit, but that parameter is already self-explanatory in the schema.

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 operation: find Korean public-data records by region and topic, with concrete examples (Gangneung libraries, Busan Jung-gu parking, Jeju tourism). It does not explicitly differentiate itself from the sibling search_catalog, which keeps it from a 5.

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?

It gives clear usage context: 'Use it for what-is-where questions' and recommends a region-plus-topic query shape. It does not state when not to use it or name alternatives, but the use case is explicit enough to guide selection.

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