Get dataset call specification

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

With no annotations, the description carries the burden of behavioral disclosure. 'Get' clearly implies a read-only operation, and listing the returned spec elements (path parameters, response fields, call example) gives useful context. However, it does not disclose error behavior, authentication requirements, or the fact that this is metadata rather than an actual data call, leaving some gaps.

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 short and front-loaded with the key information. However, the second sentence in Korean largely repeats the first sentence's meaning, which is redundant for an AI agent. It is still efficient, but not every word earns its place.

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?

Given the tool's simplicity (one parameter, no output schema), the description covers the essential aspects: what it returns, and when to use it. It does not explain return formatting or error conditions, but that is not critical for a straightforward spec-fetching tool.

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 baseline is 3. The description only mentions 'catalog dataset id' in passing and does not add semantic detail beyond what the schema already provides for the 'id' parameter. It adds no additional meaning about the parameter's format or usage.

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 a specific verb 'Get' and a clear resource 'dataset call specification', explicitly listing the return contents (path parameters, response fields, call example). It distinguishes itself from sibling data-retrieval tools by referencing call_dataset, indicating it is a preparatory metadata tool.

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 explicit when-to-use guidance: 'call_dataset 호출 전' (before calling call_dataset) and '확인합니다' (check). It implies this tool is for pre-call preparation, but it does not mention exclusions or alternative tools, so it lacks a full when-not-to-use clause.

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