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get_student_grading_bundle

Retrieves a student's AI grading bundle—grading context, manual grading items, scores, answers, and attachments—and downloads attachments to a local directory.

Instructions

获取单个学生的 AI 批改包,并下载附件到本地。

只返回 AI 批改必需字段:grading_context、需人工批改的题目、
当前分数/评语、学生答案和附件 file_path。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
group_idYes课程组id(通过 query_teacher_groups 获取)
paper_idYes试卷ID(通过 query_group_tasks 获取)
save_dirNo附件保存目录。默认使用当前系统临时目录;同一附件已下载时自动复用本地文件。
record_idYes答题记录id(来自 query_test_result 的 answer_records[].record_id 字段)
publish_idYes发布id(来自 query_group_tasks 的 publish_id 字段)
mark_mode_idYes阅卷模式id(来自 query_test_result 的 mark_mode_id 字段)
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses the side effect of downloading attachments locally and specifies the returned fields. However, it does not confirm whether the tool is read-only or if any state changes occur beyond file download.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with main action, then specifics. No redundant or extraneous content. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description compensates by listing the returned fields and mentioning attachment behavior. It lacks detail on the structure of grading_context but is otherwise sufficient for a retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with detailed parameter descriptions linking to other query tools. The description does not add extra meaning beyond listing return fields, which is output-related. Baseline 3 is appropriate since schema already thoroughly documents each parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: retrieving a single student's AI grading bundle and downloading attachments. It specifies the returned fields (grading_context, manually graded items, scores/comments, student answers, attachment file_path). This distinguishes it from siblings like grade_student_paper which perform grading actions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for obtaining grading bundle data but does not explicitly state when to use this tool vs alternatives (e.g., grade_student_paper for actual grading). No guidance on prerequisites or when not to use it.

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

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