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query_preview_student_paper

Query a single student's full answer content and retrieve answer IDs required for scoring each question.

Instructions

[批改第2步] 查询单个学生的完整答题内容,返回 mark_paper_record_id 和每道题的 answer_id(打分必需)

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)
record_idYes答题记录id(来自 query_test_result 的 answer_records[].record_id 字段)
parse_modeNo富文本解析模式:plain=纯文本,raw=原始结构,markdown=标准 Markdown + assetsplain
publish_idYes发布id(来自 query_group_tasks 的 publish_id 字段)
detail_levelNo答题粒度:summary=得分/状态,full=含答题内容summary
mark_mode_idYes阅卷模式id(来自 query_test_result 的 mark_mode_id 字段)
Behavior3/5

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

Without annotations, the description must convey behavioral traits. It states the tool queries data, implying a read-only operation. It does not disclose side effects, authorization needs, or rate limits, but for a read query this is minimally acceptable.

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?

The description is a single, front-loaded sentence that efficiently conveys purpose, step context, and key return fields. No extraneous words.

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 adequately explains what is returned (mark_paper_record_id and answer_id). It could elaborate on how parse_mode and detail_level affect output, but the schema covers their definitions. Overall sufficient for an agent in a marking workflow.

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?

All 7 parameters have descriptions in the schema (100% coverage). The description adds only minor insight: that answer_id is required for scoring. This provides marginal added value beyond the schema, meeting the baseline for high coverage.

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 is '[Marking Step 2]' and queries a student's complete answer content, returning mark_paper_record_id and answer_id for each question. This explicitly distinguishes it from sibling tools like 'grade_student_paper' which perform the actual grading.

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

Usage Guidelines4/5

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

It indicates that this tool is step 2 in a marking workflow and that its output is required for scoring. This provides clear usage context. However, it does not explicitly mention when not to use it or list alternative tools.

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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