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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), and the description adds genuinely new behavioral facts: per-call price ¥0.1, billing only on success, automatic refund on failure or empty result, and the platform visibility cap. Auth requirements and rate limits are left to the schema's _token field.

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?

Four dense sentences with no filler: purpose, return fields, use cases, then billing and a pagination caveat. Front-loaded correctly, though the billing sentence sits before the platform-limit caveat rather than after.

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 does the necessary work by enumerating returned fields and page-based delivery. The one real hole is how to continue paging, since continuation_token appears as an output but has no corresponding input parameter or instruction.

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% with only two params, so the baseline is 3. The description mentions a continuation_token for paging, but no such input parameter exists in the schema, leaving the actual pagination mechanism ambiguous rather than clarified.

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+resource ('获取YouTube视频评论') and enumerates exactly what comes back (comment text, likes, reply count, nickname, region, timestamp), so the agent knows this is a top-level comment fetch. It stops short of naming the sibling it differs from (yt_sub_comments / yt_post_detail), so the distinction is implied rather than stated.

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 explicit use cases (sentiment analysis, competitor reputation comparison, public-opinion monitoring) and a operational caveat that pagination depth is capped by the platform, after which upstream returns nothing. It does not state when NOT to use it or which sibling to pick instead for replies vs. posts.

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