Skip to main content
Glama
OSSKn4w7

chaoxing-mcp

by OSSKn4w7

cx_s_get_homework_detail

Retrieve detailed homework information including question lists, attachments, and standardEnc for a specific course assignment. Use this to inspect assignment content without auto-answering or submitting.

Instructions

读取作业详情:题目列表(题干/选项/题型)、附件列表、standardEnc。不会自动作答或提交。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workUrlYes
courseRefYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well by explicitly stating '读取' (read) and '不会自动作答或提交' (will not auto-answer or submit), conveying a read-only, non-mutating behavior. It also discloses the response contents (questions, attachments, standardEnc), though it omits authentication prerequisites or rate limits.

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 states the action and enumerates the returned content, followed by a concise safety clarification. Every word earns its place without fluff.

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?

The description covers purpose, content, and non-mutation, and an output schema exists to define return values. However, it does not explain how to obtain or supply workUrl and courseRef, nor does it explicitly guide selection among sibling tools, leaving moderate ambiguity for a two-parameter call.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must compensate for the undocumented workUrl and courseRef parameters, but it never mentions them or explains how they are used. The only weak inference is that one parameter identifies the homework, which is insufficient for correct invocation.

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 specifies a clear verb and resource: '读取作业详情' (read homework details), and enumerates exact content: question list (stem/options/type), attachment list, and standardEnc. It also differentiates from siblings by explicitly stating it will not auto-answer or submit, positioning it apart from cx_s_submit_homework.

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 when to use the tool—when you need a homework's question list, attachments, or standardEnc—but it does not explicitly state selection conditions or positive alternatives. The only contrast is the negative '不会自动作答或提交', which serves as a behavioral disclaimer rather than routing guidance.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/OSSKn4w7/chaoxing-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server