대학 검색·지표

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

With no annotations, the description must disclose behavioral traits but only describes the query action as a data retrieval. It does not state that it is read-only, whether side effects exist, if authentication is required, or how results are paginated. The source mention provides some trust but not behavioral clarity.

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 well-formed sentence that front-loads the main action and lists the key indicators. It includes a source attribution without unnecessary words. However, it could be slightly more structured (e.g., separating the list of indicators) for easier parsing.

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 has 5 optional parameters, no output schema, and no annotations, the description is incomplete. It does not mention that all parameters are optional, what the default search returns, or the format of results. Key details like pagination, result count, or data structure are missing, leaving the agent uncertain about how to interpret the output.

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 description adds no parameter-level details beyond the input schema. Although schema coverage is 60%, the description does not explain how region, field, establishment, majorName, or year affect the search. For parameters without schema descriptions (establishment, majorName), the description offers no compensation, leaving ambiguity about their meaning or allowed values.

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 that the tool searches for universities with department offerings and returns key indicators (competition rate, tuition, etc.), using a specific verb '조회합니다' (inquire/retrieve). It distinguishes from siblings like search_major (which likely focuses on departments) by mentioning both universities and specific indicators, but it does not explicitly contrast with other tools.

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 no guidance on when to use this tool versus alternatives like search_major, explore_job, or get_major. There is no mention of prerequisites, conditions that trigger use, or cases where this tool is inappropriate. The agent must infer usage entirely from the name and sibling context.

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