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传承·交大 MCP

传承·交大 MCP

by Flagwill
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

share_upload_material

Destructive

Upload local files to create shared course materials with metadata, optional points, and anonymous or named submission.

Instructions

上传本地文件并创建资料：申请票据、上传对象存储、提交元数据。最大 100 MB，价格 0–10，默认匿名且免费。confirm=true 执行。

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": {
      "file_path": "<file_path>",
      "course_id": "<course_id>",
      "class_id": "<class_id>",
      "material_type_id": "<material_type_id>",
      "name": "<name>"
    },
    "name": "share_upload_material"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
pointsNo
confirmNo确认用户已授权此次操作后设为 true
class_idYes平台对象 ID，正整数
anonymousNo
course_idYes平台对象 ID，正整数
file_pathYes
descriptionNo
material_type_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

A3.7/5.0
Behavior4/5

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

Annotations already declare a non-read-only, open-world, destructive operation. The description adds useful behavioral context beyond that: the internal ticket/upload/metadata workflow, the 100 MB size cap, default anonymous and free behavior, and the confirm=true execution requirement.

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 compact and front-loaded, packing the workflow, limits, defaults, and execution gate into a few dense clauses without wasted text.

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

Completeness3/5

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

For a 9-parameter mutation with 5 required parameters and low schema description coverage, the description covers the high-level flow and safety gate but omits important context about how to choose the required course, class, and material type IDs. Output schema exists, so return values need not be explained.

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 description coverage is only 44%, so the description must compensate. It does clarify file upload, points range, anonymous/free defaults, and confirm execution, but it leaves required parameters such as name, course_id, class_id, and material_type_id largely unexplained.

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

Purpose4/5

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

The description states a specific verb and resource: uploading a local file and creating a material, with the internal steps (ticket, object storage, metadata). It is clearly distinguishable from siblings like update_material or download_material, though it does not explicitly name alternatives.

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?

Usage is implied by the upload/create framing and the confirm=true execution gate, but there is no explicit guidance on when to use this instead of related tools such as update_material, or on prerequisites like obtaining course/class/material_type IDs.

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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