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

The annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is covered. The description adds valuable behavior that the annotations do not: billing at ¥0.2 per call, charge only on success with automatic refund on failure or empty results, and a pagination-depth ceiling imposed by the platform after which the upstream stops returning data. Those cost and failure-handling disclosures are genuinely useful, but the scoring rubric reserves higher scores for richer operational detail, and the description omits rate limits or return-order specifics.

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 definition is dense and front-loaded: purpose first, then returned fields, use cases, cost, and paging caveat in that order. Every sentence adds distinct information, and there is no repetition of the name or title and no 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?

The tool has no output schema, but the description compensates by enumerating the returned fields, including comment text, likes, replies, author nickname and region, and timestamp. It also discloses the cost model and the pagination-depth limit, which an agent needs in order to avoid wasted calls. Nothing essential for correct invocation is missing.

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%, so all three parameters, _token, cursor, and photo_id, are already documented in the schema. The description only implies page-based paging through '按页返回' and adds no cursor syntax, page size, or token-placement guidance beyond what the schema states. The baseline of 3 is appropriate when the schema carries the parameter documentation.

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 uses a specific verb and specifies a precise resource, namely '获取快手视频评论列表', and it scopes the result to one video through the required photo_id. It lists the returned fields, so an agent knows exactly what data it will receive. It does not explicitly distinguish this tool from siblings such as ks_sub_comments, which retrieves replies, so it stops short of a 5.

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 gives clear intended contexts: '做评论情感分析、竞品口碑对比或舆情监测时用'. That is enough for an agent to recognize the right scenario. However, it names no alternatives or exclusions, such as routing to ks_sub_comments for reply threads, and states no prerequisites for getting the video ID first.

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