Look up department office phone numbers and professor or staff contact details in Ulsan University's phone directory to find the right campus contact.
학부·학과 사무실 전화번호와 교수·직원 연락처표(본교 전화번호 안내). 2025 신설 학부는 위치가 비어 있을 수 있어 dept_site(학부, '찾아오시는길')로 학부 홈페이지에서 확인한다.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden alone. It discloses the valuable data quality caveat that newly created 2025 departments may have empty location fields, but doesn't state whether the tool is read-only, what the output table looks like, or coverage limits.
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?
Two sentences, front-loaded with what the tool returns, followed by the caveat and fallback. Every sentence carries signal, though the fallback sentence is slightly compressed and could be clearer.
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?
Output schema exists, so return values needn't be explained, and the data caveat is a helpful addition. However, with zero schema coverage on the sole parameter and no annotations, the description should clarify the input's expected meaning to be 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?
Single parameter 'name' has 0% schema description coverage, and the description never clarifies whether 'name' is the department name or a person's name. The dept_site(dept, ...) reference hints at department names, but this is inferential rather than explicit.
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?
States a specific resource: department office phone numbers and a professor/staff contact table. An agent can tell it apart from dept_site or departments, though the description doesn't name what distinguishes it from the plain 'departments' sibling.
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?
Gives a concrete fallback rule: for 2025 newly established departments where location may be blank, use dept_site(dept, '찾아오시는길'). That is useful guidance for missing data, but there is no explicit 'use this when X, not Y' for the core lookup versus other siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.