查询用户姓名

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

With no annotations, the description carries the full burden of behavioral disclosure. It does not explicitly state that this is a read-only operation, nor does it mention possible errors (e.g., student not found) or any restrictions implied by '固定学号'. The lack of detail leaves behavioral traits opaque.

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 concise sentence that immediately conveys the purpose. There is no redundancy or extraneous information, and the key information is front-loaded.

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?

For a simple lookup tool with an output schema, the description provides the basic purpose. However, the ambiguous phrase '固定学号' could confuse the agent about whether the ID is hardcoded or a parameter. Missing usage context and error behavior make it only minimally viable for the tool's simplicity.

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 coverage is 0%, so the description must compensate by explaining the parameter. However, it only mentions '学号' (student ID) in passing without clarifying format, range, or acceptable values. This adds minimal meaning beyond the parameter name 'studentId' already visible in the schema.

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 action (查询/query) and resource (用户姓名/user name), with the qualifier 根据固定学号 (based on fixed student ID). This distinguishes it from sibling tools like calculate_average and evaluate_score, which are calculation-oriented.

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?

No guidance is given about when to use this tool versus the siblings. There is no mention of exclusions, prerequisites, or alternative tools. The usage context is only implied by the tool's obvious purpose, but no explicit guidance is provided.

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