Skip to main content
Glama
Wanyi424
by Wanyi424

extract_douyin_text

Extract text content from Douyin (TikTok) videos using share links, supporting optional speech recognition models for transcription.

Instructions

从抖音分享链接提取视频中的文本内容

参数:
- share_link: 抖音分享链接或包含链接的文本
- model: 语音识别模型(可选,默认使用paraformer-v2)

返回:
- 提取的文本内容

注意: 需要设置环境变量 DASHSCOPE_API_KEY

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
share_linkYes
modelNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It reveals the tool performs extraction (likely involving video processing and speech recognition), mentions an optional model parameter with default, and discloses the API key requirement. However, it doesn't describe rate limits, error conditions, processing time, or what happens with invalid links. The behavioral information is basic but not comprehensive.

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 well-structured with clear sections (purpose, parameters, return, note) and appropriately sized. Each sentence adds value: the purpose statement, parameter explanations, return specification, and environment requirement. It's front-loaded with the core functionality. Minor improvement could be making the purpose statement slightly more distinctive from siblings.

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?

Given the tool has 2 parameters (1 required), 0% schema description coverage, no annotations, but has an output schema, the description provides good contextual coverage. It explains both parameters' semantics, mentions the return value, and discloses the API key requirement. The output schema existence means the description doesn't need to detail return structure. For a tool of this complexity, it's reasonably complete though could benefit from more behavioral context.

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

Parameters4/5

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

The description adds significant semantic value beyond the 0% schema description coverage. It explains that share_link accepts '抖音分享链接或包含链接的文本' (Douyin share link or text containing link), clarifying it's not just a URL but can include surrounding text. For the model parameter, it specifies '语音识别模型' (speech recognition model) with default 'paraformer-v2', explaining its purpose when the schema only shows it as optional string/null. This compensates well for the schema's lack of descriptions.

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 tool's purpose: '从抖音分享链接提取视频中的文本内容' (extract text content from Douyin video share links). It specifies the verb '提取' (extract) and resource '文本内容' (text content) from Douyin videos. However, it doesn't explicitly differentiate from sibling tools like parse_douyin_link, which might parse metadata rather than extract text.

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 usage context through the parameter explanation and note about API key requirements, but doesn't explicitly state when to use this tool versus alternatives like parse_douyin_link or parse_generic_link. The mention of '需要设置环境变量 DASHSCOPE_API_KEY' (requires setting DASHSCOPE_API_KEY environment variable) provides some prerequisite guidance, but no explicit when/when-not instructions.

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/Wanyi424/wanyi-watermark'

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