scienceon_researcher_details

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

The description says '조회' (query), which is consistent with readOnlyHint=true, and adds that it returns '상세정보' (detailed information). It does not disclose other behavioral aspects such as error conditions or response format, but the output schema covers return values.

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 a single front-loaded sentence that directly states the operation and key identifier, containing no unnecessary words or repetition.

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 simple lookup nature, a fully described required parameter, readOnlyHint annotation, and an available output schema, the one-line description is sufficient for an agent to select and 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?

The input schema has 100% coverage, describing cn as the researcher's unique identifier from search results. The tool description only repeats 'CN번호로' without adding further semantic detail, so the baseline of 3 is appropriate.

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 '조회' (retrieve) with the resource '연구자 상세정보' and the method 'CN번호로', clearly defining a detail-lookup operation. It distinguishes itself from the sibling 'scienceon_researchers' search tool by requiring an existing CN identifier.

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 parameter schema states cn comes from '연구자 검색 결과의 CN 값' (CN value from researcher search results), implying this tool is used after a search to get full details. It does not explicitly name alternatives, but the intended post-search workflow is clear.

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