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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely new behavior: unit price ¥0.1 per call, billing only on success, and automatic refund on failure or empty result. It does not discuss authentication (the schema's _token field implies an auth requirement) or rate limits, so it adds value but not rich context.

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?

Three sentences with no waste: purpose and return payload first, then usage scenarios, then billing terms. Front-loaded and each sentence carries distinct 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?

With no output schema, enumerating the returned fields is the right compensating move, and billing semantics are covered. The remaining gap is sibling disambiguation against douyin_video_detail and douyin_video_like_count, which matters given how many near-duplicate douyin tools exist.

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 description coverage is 100%, and both parameters (aweme_id, _token) are documented in the schema, so the baseline is 3. The description contributes nothing about parameter format, ID provenance, or the token fallback, leaving the schema to carry all parameter meaning.

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?

States a specific verb and resource ('获取抖音视频播放量') and then enumerates the returned fields (title, like/comment/collect/share counts, author nickname and sec_uid, publish time, cover, BGM). That is far clearer than the name alone, which would suggest only a play-count metric. It does not, however, distinguish itself from close siblings such as douyin_video_detail or douyin_video_like_count, which appear to overlap.

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?

Gives concrete usage scenarios: single-item engagement analysis, material archiving, or as the starting point of a batch job. That tells an agent when the tool fits. It stops short of exclusions or naming an alternative (e.g. use douyin_video_comments for comment text), so it does not reach a 5.

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