fields

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

The description adds behavioral context beyond the readOnlyHint annotation: it specifies the matching logic ('ALL named columns') and the return type ('ranked metadata as in search'). This gives the agent a clear expectation of the tool's behavior and output without contradicting the read-only annotation. The description does not repeat the annotation but enriches it.

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 concise and front-loaded with the core purpose, followed by parameter examples and return info. Each sentence serves a purpose, though the bilingual repetition (Korean then English) adds slight redundancy. Overall, it is efficient and well-structured.

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 presence of an output schema and the readOnlyHint annotation, the description does not need to elaborate on return values or safety. It covers parameter semantics, matching logic, and return type. It does not mention pagination or ordering, but these are minor for a search tool. The description is sufficiently complete for an agent to invoke the tool correctly.

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 0%, but the description compensates by providing concrete examples and constraints for each parameter: 'names 예시 / Example: ['위도', '경도']; n: 1~20; dtype: FILE/API/STD; org: 기관명.' This clarifies the format, allowed values, and meaning of parameters, which the schema alone does not convey. It does not explain what 'STD' stands for, but the given options are sufficient for basic 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 clearly states the tool's purpose: 'Find datasets matching ALL named columns.' This is a specific verb (find) + resource (datasets) + condition (matching ALL named columns). It distinguishes itself from siblings like search by focusing on column-based matching, making its intent unmistakable.

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 examples for parameters (names, n, dtype, org) and mentions it returns metadata 'as in search,' implying it is used when you have specific column names. However, it does not explicitly state when to use this tool over alternatives like search or when not to use it. The usage context is implied rather than explicitly stated.

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