Skip to main content
Glama

编辑LMS单元

classin_update_unit
Idempotent

Update LMS learning unit details by specifying unit ID and optionally changing its name, description, or publication status.

Instructions

编辑LMS学习单元信息。

参数:

  • unitId: 单元ID

  • name: 新的单元名称(可选)

  • content: 新的单元介绍(可选)

  • publishFlag: 新的发布状态(可选)

返回:

  • 成功返回操作结果

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo新的单元名称
unitIdYes单元ID
contentNo新的单元介绍
publishFlagNo发布状态: 0=草稿, 2=已发布
response_formatNo输出格式: 'markdown' 人类可读格式 或 'json' 机器可读格式markdown
Behavior3/5

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

Annotations already cover read/write (readOnlyHint=false), idempotency, and destructiveness, so the description need not repeat those. It adds that only unitId is required and the other fields are optional, plus a success return, but does not describe side effects or response details.

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

Conciseness4/5

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

The description is concise and front-loaded with its purpose, followed by a compact parameter list and return note. It could be slightly tighter by not repeating schema details, but there is no wasted or misleading content.

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?

With five parameters and no output schema, the description gives only a vague '成功返回操作结果' (returns operation result on success) and does not explain the response_format option or error behavior. However, the rich schema and annotations fill in many gaps, making it minimally viable.

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 100%, so the baseline is 3. The description's parameter list mostly repeats schema information (unitId, name, content, publishFlag) and adds 'optional' labels, but it does not provide extra semantics 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 opens with '编辑LMS学习单元信息' (Edit LMS unit information), a specific verb and resource that clearly states the tool's function. It is distinct from sibling tools such as classin_create_unit and classin_delete_unit.

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 this is for modifying an existing LMS unit, but it does not explicitly state when to use it versus creating or deleting a unit. No alternative tools or exclusions are mentioned.

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

Install Server

Other Tools

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/yuanlang12/classin-mcp-server'

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