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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds real operational context beyond them: ¥0.2 per successful call only, automatic refund on failure or empty result, and a pagination depth cap imposed by the upstream platform. It does not mention auth expectations, and the depth cap is stated without saying how pagination behaves at the boundary.

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?

Front-loaded with purpose and payload, then use cases, then billing, then the depth caveat — a sensible priority order with no filler. It is dense but each sentence (fields, use cases, pricing, cap) supplies information an agent would otherwise lack.

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 read-only paged list tool with no output schema, the description covers return contents, intended analyses, cost/refund behavior, and the coverage ceiling — enough to call it correctly. The remaining gap is sibling disambiguation against zhihu_sub_comments and any auth hint, both minor here.

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 limit/offset/answer_id/_token are already documented, and the baseline is 3. The description only implicitly adds that results are paged (按页返回), giving mild extra meaning about how offset/limit pair with the platform depth limit, but no format or syntax detail beyond the schema.

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?

Names a specific verb+resource (获取知乎回答评论列表) and enumerates what comes back (评论正文、点赞数、回复数、评论者昵称与地区、时间戳). It is clearly distinct from sibling detail/search tools, but it never distinguishes itself from zhihu_sub_comments, the sibling most likely to be confused with it.

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 use cases (评论情感分析、竞品口碑对比、舆情监测) that tell the agent when this tool fits. It stops short of exclusion guidance — there is no 'use zhihu_sub_comments instead when you need replies-to-replies' routing statement.

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