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

Beyond the read-only/idempotent annotations it discloses genuinely useful operational facts: page-based pagination with a cursor, per-call pricing at ¥0.2, billing only on success with automatic refunds on failure or empty results, and that pagination depth is capped by platform visibility. Auth handling is only implied via the schema's _token parameter, and no rate limits are mentioned.

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 tight sentences: what it returns first, then use cases, then cost and limits. Every clause carries information (fields, billing policy, pagination ceiling) and nothing is repeated from the schema.

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?

There is no output schema, yet the description lists the return fields, explains pagination mechanics and its ceiling, and covers billing behavior on failure. That is everything an agent needs to decide to call it and interpret an empty page.

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 post_id, count, max_id and _token are already documented. The description only reinforces the pagination concept ('按页返回', depth limits) without adding format or syntax detail, which is the expected baseline when the schema does the work.

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 opening sentence names a specific verb and resource ('获取微博帖子评论列表') and enumerates the returned fields. It is clear on its own, but it never distinguishes itself from the closely named sibling weibo_sub_comments, leaving the agent to infer the top-level vs. reply-level split.

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?

It gives three concrete use contexts (sentiment analysis, competitor word-of-mouth comparison, public-opinion monitoring), which tells the agent when this tool is a fit. It stops short of stating when not to use it or naming the alternative tool for nested replies.

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