Grade an individual homework submission by entering a score and rich-text feedback, optionally marking it as a model example and notifying the student by email.
為個別學生的繳交作業填入批改分數、富文字評語、是否標示為值得觀摩，以及是否寄信通知學生
| Name | Required | Description | Default |
|---|---|---|---|
| reportId | Yes | 繳交紀錄 ID (reportId) | |
| auditScore | Yes | 給予分數（例如 88） | |
| commentHtml | Yes | 批改評語（支援富文字 HTML 標籤，例如 <p>論述完整清晰</p>） | |
| isModelStudent | No | 是否勾選為值得觀摩範例 | |
| sendEmailNotification | No | 是否寄送通知信給繳交學生 |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses that it writes grading fields and can optionally send an email notification, which is useful side-effect context, but it says nothing about permissions, reversibility, whether existing scores can be overwritten, or what happens if the submission has already been audited.
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 with no filler, and it enumerates the main fields concisely. It is efficient, though very dense and lacking structure for the optional side-effect parameter.
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 five-parameter mutation tool with no annotations and no output schema, the description leaves important gaps: prerequisites, required vs optional fields, validation/error behavior, overwrite semantics, and the precise effect of sending email. The schema covers parameter details, but behavioral completeness is weak.
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 description coverage is 100%, so the schema already defines all five parameters with examples and defaults. The description echoes the fields (score, comment, exemplary flag, email notification) but adds no format constraints, validation rules, or default behavior beyond what the schema provides.
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 states a specific action on a specific resource: filling in grading score, rich-text comment, exemplary flag, and email notification for an individual student's homework submission. It is clear what the tool does, but it does not explicitly differentiate itself from siblings such as reject_homework_submission or audit_essay_question.
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 explicit when-to-use conditions, prerequisites, or alternative tools. Usage is only implied by 'individual student's submission' and the fact that it fills in grading fields; there is no guidance on when to choose this over reject_homework_submission or audit_essay_question.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.