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undoom-douyin-data-analysis

undoom-douyin-data-analysis

by kk520879
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

export_data

Export collected Douyin video and user data in JSON, Excel, or CSV format for further analysis.

Instructions

导出采集的数据

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "export_data"
  }
}

Input Schema

NameRequiredDescriptionDefault
formatNo导出格式json
data_typeNo导出数据类型videos
filenameNo文件名（不包含扩展名）douyin_data

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.3

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits. It only states 'export collected data' without clarifying whether the operation is destructive, requires authentication, or has any side effects. The agent is left to assume it's a safe read-export, but this is not explicit.

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 extremely concise (one short phrase), with no unnecessary words. However, it is so brief that it may omit essential context, such as export format options or behavioral notes. It earns a high conciseness score but loses a point for not providing enough substantive content in its structure.

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

Completeness2/5

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

The description lacks contextual completeness for a data export tool with three parameters and no output schema. It does not explain what happens after export (e.g., file download, storage location) or how the output is delivered. It also does not reference related tools like clear_data for post-export cleanup. The agent may not understand the full workflow.

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 covers all three parameters with descriptions and defaults (format, data_type, filename). Since schema coverage is 100%, the description does not need to add parameter details. It adds no extra semantic context beyond what the schema provides, so a 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 verb 'export' and the resource 'collected data', but it lacks specificity about what types of data (videos, users) and formats, and does not differentiate from siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus its siblings (e.g., when to export vs analyze or search). It does not specify prerequisites or alternatives.

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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