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 the annotations cannot express: the per-call price (¥0.2/次), that only successful calls are billed, and that failures or empty results are auto-refunded — material for an agent deciding whether to retry. It says nothing about rate limits or failure modes beyond billing.

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, each doing distinct work: what it returns, when to use it, what it costs. Front-loaded with the resource and payload before the use cases, with 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?

With no output schema, the description carries the return-shape burden and does so by listing the returned fields. Cost and billing behavior round it out for a simple 2-parameter read tool. The only gap is that it does not say where photo_id values normally come from, which matters given the many sibling search tools.

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 are documented, including the _token alternative-auth note, so the baseline is 3. The description adds no meaning beyond the schema — it never mentions photo_id format, where an ID typically comes from (e.g. ks_keyword_search or ks_user_posts), or granularity of the returned counts.

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 (获取快手视频详情) and enumerates the payload returned — 作品描述、点赞/评论/播放数、作者信息、封面、发布时间 — which functionally separates it from ks_post_comments and ks_user_posts. It stops short of naming those siblings, so the differentiation is inferred rather than explicit.

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 three concrete scenarios: 单条内容的互动量分析, 素材入库, 作为批量任务起点. That is clear when-to-use context. There are no exclusions or explicit pointers to alternative tools (e.g. when you already know the author and want their feed, use ks_user_posts), so it falls shy of a 5.

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