extract_douyin_text

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 successfully reveals several important behavioral traits: the tool performs text extraction from video content, requires an API key (DASHSCOPE_API_KEY environment variable), uses speech recognition (implied by the model parameter), and has an optional model parameter with a default. However, it doesn't mention rate limits, error conditions, or authentication details beyond the API key requirement.

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

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

The description is well-structured with clear sections (purpose, parameters, returns, notes) and uses only essential sentences. Each section earns its place by providing distinct information. The Chinese text is concise and direct, though the formatting with section headers could be slightly more polished.

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

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

Given the tool's moderate complexity (2 parameters, speech recognition functionality) and the presence of an output schema (which handles return values), the description provides good contextual coverage. It explains the core functionality, parameters, authentication requirement, and basic workflow. The main gap is lack of error handling information and more detailed model options.

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

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

With 0% schema description coverage, the description must compensate. It provides meaningful semantic context for both parameters: 'share_link' accepts Douyin share links or text containing links, and 'model' specifies the speech recognition model with a default value. This adds substantial value beyond the bare schema, though it could provide more detail about valid model options or link formats.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('从抖音分享链接提取视频中的文本内容' - extract text content from Douyin share links) and the resource (Douyin video content). It distinguishes itself from sibling tools like 'get_douyin_download_link' and 'parse_douyin_video_info' by focusing specifically on text extraction rather than downloading or general video information parsing.

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

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

The description implies usage context through the mention of Douyin share links and the optional model parameter, but doesn't explicitly state when to use this tool versus the sibling tools. There's no guidance about alternative approaches or specific scenarios where this tool is preferred over 'parse_douyin_video_info' which might also provide text information.

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