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传承·交大 MCP

传承·交大 MCP

by Flagwill
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

share_list_course_classes

Read-onlyIdempotent

List teaching classes, instructors, and material counts for a course to obtain the class ID required for uploading shared resources.

Instructions

列出课程的教学班、教师及资料数量；上传时需要 class_id。

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "course_id": "<course_id>"
    },
    "name": "share_list_course_classes"
  }
}

Input Schema

NameRequiredDescriptionDefault
course_idYes平台对象 ID，正整数

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive behavior, and openWorldHint. The description adds useful context beyond the annotations by specifying what the response contains (classes, teachers, material counts) and the upload-related workflow it supports.

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 extremely compact: one sentence with two clear clauses, front-loading what is listed and then the upload prerequisite. Every clause contributes useful information.

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

Completeness5/5

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

For a simple, fully specified read operation with an output schema and rich annotations, the description is complete enough to call correctly. It covers the resource, returned content, and the primary workflow reason to use it.

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?

There is only one parameter, course_id, and schema description coverage is 100%, so the schema already documents it as a positive integer platform object ID. The description implies a course context but adds no syntax or format details beyond the schema.

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 states a specific verb-resource pair: it lists a course's teaching classes, teachers, and material counts. It also adds the distinctive operational detail that the returned class_id is required for uploading, which separates it from siblings such as material-listing tools.

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?

The description clearly identifies the key usage scenario: call this when a class_id is needed before an upload. It does not name alternatives or state when not to use the tool, so it falls short of explicit when/when-not guidance.

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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