submit_student_mark

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

Without annotations, the description carries full burden. It discloses key behaviors: success writes scores to the student side (persistence), dependency on prior grading of all manual questions, and the need to withdraw before modifications. However, it does not mention error conditions or idempotency.

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 with only two sentences plus a preamble. It is front-loaded with the purpose in brackets, and every sentence adds value with no redundant information.

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 lack of annotations and output schema, the description covers prerequisites, effects, and related tools. It could mention potential error states or return values, but it is largely complete for a submission action.

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 covers 100% of parameters with descriptions explaining source values (from other tools). The tool description does not add further parameter semantics beyond what the schema provides, so a baseline score 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 clearly states the tool's purpose: '提交整卷批阅结果' (submit entire paper marking results). It distinguishes itself from sibling tools like 'grade_student_question' (grades individual questions) and 'withdraw_student_mark' (reopens grading for modifications). The title and name also reinforce this purpose.

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 explicit usage guidance: it must be called after all manually graded questions have been processed via 'grade_student_question', and if modifications are needed, 'withdraw_student_mark' must be called first. This covers when and how to use the tool, though it does not list alternative tools for other scenarios.

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