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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint, so the safety profile is covered. The description does add genuinely non-structured context: a per-call price of ¥0.1, billing only on successful calls, and automatic refund on failure or empty results — useful for cost-sensitive agents. It says nothing about rate limits, freshness of the counts, or how an invalid aweme_id surfaces, so it stays at an adequate rather than rich level.

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, front-loaded with the core action, then the return payload, then the use case and pricing. The return-field enumeration is dense but each item is informative rather than filler. Slightly long for a two-parameter tool, but nothing is clearly wasted.

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, the description correctly takes on responsibility for describing return fields and does so thoroughly, plus it discloses the billing model. What's missing for a tool inside an 80+ sibling catalogue is routing guidance versus douyin_video_detail and douyin_video_play_count, which would make the definition fully self-sufficient.

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%, so both properties (aweme_id, _token) are already documented in the schema. The description adds no format, ID-shape, or accepted-value guidance for aweme_id beyond the phrase 视频. Baseline 3 applies since the schema carries this dimension.

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 (获取抖音视频点赞数) and enumerates exactly what comes back — title text, like/comment/collect/share counts, author nickname and sec_uid, publish time, cover and BGM. That makes the tool's surface concrete without opening the schema. It never names or contrasts with the close siblings douyin_video_detail and douyin_video_play_count, so an agent must infer which one to pick from the field list alone.

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 when-to-use triggers: single-item engagement analysis, asset-library ingestion, or as the starting point for a batch task. No exclusions or alternatives are mentioned, so it doesn't resolve the overlap with douyin_video_detail, which is the case an agent is most likely to get wrong.

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