TikTok MCP

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes what the tool does (looks up available subtitles) and the return content (languages and formats like ASR, Machine Translation, Creator Captions). However, it lacks critical behavioral details such as error handling (e.g., what happens if no subtitles are available), rate limits, authentication requirements, or performance characteristics. For a tool with no annotations, this is a significant gap.

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 moderately concise but has structural issues: it's a single run-on sentence with awkward phrasing ('differentformats') and lacks clear front-loading of key information. While it covers purpose, usage, input, and output, the flow could be improved for better readability. Some sentences could be trimmed or rephrased to be more direct.

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 (1 parameter, no output schema, no annotations), the description is partially complete. It explains the purpose, input, and output (subtitles in various languages/formats), but misses behavioral aspects like error cases or operational constraints. Without annotations or output schema, the description should ideally cover more ground to fully inform the agent, leaving some gaps in completeness.

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 100% description coverage, with the parameter 'tiktok_url' well-documented in the schema. The description adds minimal value beyond the schema: it mentions 'Supports TikTok video url as input in object' and implies the URL is used to look up subtitles, but doesn't provide additional semantics like URL validation rules or examples beyond what's in the schema. With high schema coverage, 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.

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

The description clearly states the tool's purpose: 'Looks up the available subtitle... for a TikTok video' with a specific verb ('looks up') and resource ('subtitle for a TikTok video'). It distinguishes from sibling 'tiktok_get_subtitle' by focusing on availability and format/language options rather than just retrieving a subtitle. However, it doesn't explicitly differentiate from 'tiktok_get_post_details' which might overlap in functionality.

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: 'This is used for looking up if there is any content (subtitle) available to a TikTok video.' It suggests when to use this tool (to check subtitle availability and formats) but doesn't provide explicit guidance on when to choose this over sibling tools like 'tiktok_get_subtitle' or 'tiktok_get_post_details'. No exclusions or alternatives are mentioned.

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