douyin_video_stats

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

Annotations carry only a title, so the description bears the full disclosure burden and does deliver real behavioral information: if the work is not on the first page it silently falls back to public data, and play counts are not public for non-owners. That fallback caveat is exactly the kind of non-obvious behavior an agent needs, though the return format and any login/auth requirement are left implicit.

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?

Two short sentences, scoping and returned fields first, then the fallback caveat — nothing is repeated from the title and no sentence is filler.

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?

For a one-parameter read tool with no output schema, the description covers scope, metrics, and the important degraded-mode behavior. The remaining gap is the shape of the returned data and whether creator-center access requires a prior login, which the agent must infer.

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?

Schema coverage is 100% for the single parameter, and the schema itself documents awemeId as a 19-digit numeric string. The description adds no further syntax, format, or lookup guidance for the ID, so the baseline of 3 applies.

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 names a specific verb and resource ('查自己某条作品...的数据') and enumerates the returned metrics (播放/点赞/评论/分享), so the agent knows this is single-work creator analytics rather than a listing like douyin_my_videos. It stops short of explicitly naming the sibling it contrasts with, but the '某条' (single item) scoping does the differentiation work.

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?

'查自己某条作品' implies the precondition that you must be the owner and are querying one already-known awemeId, which is useful selection context. There is no explicit statement of when not to use it, nor a named alternative for listing all works or for other users' videos, so the guidance remains implied rather than stated.

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