parse_douyin_link

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: automatic type detection (video/image), returns JSON with resource links and info, includes fallback to generic logic on failure, and specifies output formatting requirements (plain text with specific fields). It also notes that Douyin only returns caption fields, and titles need to be supplemented by the caller. However, it doesn't cover potential rate limits, authentication needs, or error handling details beyond the fallback mention.

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 appropriately sized but not optimally structured. It front-loads the core purpose but mixes parameter details, return format instructions, and behavioral notes in a somewhat dense paragraph. Sentences like '调用完成后，请将结果整理为以下纯文本格式并反馈给用户（禁止使用Markdown）' are verbose and could be streamlined. However, all content is relevant, with no redundant information.

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 1 parameter, no annotations, and an output schema (implied by '返回' details), the description is mostly complete. It covers purpose, parameter semantics, return format, and key behaviors like fallback logic. The output schema existence means it doesn't need to fully explain return values, but it still provides useful formatting instructions. Minor gaps include lack of error details or performance considerations.

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?

The input schema has 1 parameter with 0% description coverage, so the description must compensate. It adds meaningful semantics: 'share_link: 抖音分享链接或包含链接的文本' (Douyin share link or text containing a link), clarifying that the parameter can accept either a raw link or embedded text. This goes beyond the schema's basic 'string' type, though it doesn't detail format constraints like URL patterns.

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 tool's purpose: '解析抖音分享链接，自动识别视频或图文类型并返回无水印资源' (parse Douyin share links, automatically identify video or image/text types, and return watermark-free resources). It specifies the exact resource (Douyin share links) and distinguishes from siblings like parse_xhs_link (for Xiaohongshu) and parse_generic_link (generic fallback).

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 provides clear context for when to use this tool: for parsing Douyin share links to get watermark-free resources. It mentions that if dedicated parsing fails, it will try generic fallback logic, implying parse_generic_link as an alternative. However, it doesn't explicitly state when NOT to use it versus siblings like extract_douyin_text (which might handle text extraction differently).

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