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MCPaeroedu

MCPaeroedu

Official
by aerovfx
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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aeroedu_question_create_bulk

Create up to 50 questions in bulk for the question bank, with active status and teacher attribution. Streamlines importing AI-generated questions from documents.

Instructions

Tạo nhiều câu hỏi cùng lúc vào Ngân hàng câu hỏi (tối đa 50 câu/lần). Lý tưởng sau khi Claude sinh câu hỏi từ tài liệu → import hàng loạt. Câu hỏi sẽ có trạng thái 'Hoạt động' và gắn tên GV tạo.

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": {
      "subject": "<subject>",
      "grade": "<grade>",
      "questions": "<questions>"
    },
    "name": "aeroedu_question_create_bulk"
  }
}

Input Schema

NameRequiredDescriptionDefault
subjectYesMôn học chung cho toàn batch
gradeYesLớp chung cho toàn batch
questionsYesDanh sách câu hỏi (1-50 câu)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

A4/5.0
Behavior4/5

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

The description reveals that created questions automatically get 'Active' status and are attributed to the teacher, and it specifies the batch size limit of 50. These details go beyond the minimal annotations (all false) and help the agent understand side effects.

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 at two sentences, clearly front-loading the main purpose and then adding the use case and behavioral outcomes. Every sentence adds value, making it efficient and well-structured.

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?

The description covers the essential aspects: purpose, batch limit, and resulting state. However, it does not describe the return value or potential errors. Given no output schema, a minor gap exists, but overall it is adequate.

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?

The input schema already provides full descriptions for all parameters (100% coverage). The tool description adds no additional parameter-level documentation beyond reiterating the max 50 constraint. Hence, the baseline score of 3 is appropriate.

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 clearly states the purpose: creating multiple questions into the question bank, with a batch size limit. It is unambiguous and distinguishable from sibling tools by function, though no explicit comparison is made.

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 provides a specific use case: batch import after Claude generates questions from documents. This gives clear context on when to use the tool, though it does not mention alternatives or when not to use it.

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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