공공데이터셋 상세와 연결 레코드

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

The annotations already declare the read-only, idempotent, non-destructive nature. The description adds behavioral context by listing exactly which fields are returned and which are omitted (source description, fields, contact info, actual values, join keys). This goes beyond annotations by clarifying the tool's scope.

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 two short sentences. The first sentence lists the returned fields, the second states exclusions. Every word is information-dense 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?

For a simple detail-retrieval tool with one parameter and no output schema, the description covers the purpose, the data returned, and the exclusions. It could have mentioned that the ID must originate from `search_public_datasets`, but it is strongly implied. Given the tool's simplicity, this is sufficiently 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?

The schema only provides the parameter name (`dataset_id`) and type/length constraints. The description adds crucial semantic meaning by identifying it as a 'search result ID', clarifying that it must come from a previous search operation. This fully compensates for the 0% schema description coverage.

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 uses the specific verb '조회합니다' (retrieves) and enumerates the exact data fields returned (data type, institution, classification, format, update cycle, keywords, official link). It also explicitly states what is not included, which helps differentiate it from tools that return full dataset content. This makes the purpose unambiguous and distinguishes it from sibling tools like search_public_datasets.

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 phrase '검색 결과 ID로' indicates that this tool is intended for use after obtaining an ID from a search result, providing clear context for when to call it. However, it does not explicitly name alternative tools or state exclusions (e.g., 'use this instead of X'). The condition is implied, not fully explicit.

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