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

The annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint), and the description adds genuinely new context: per-call pricing of ¥0.1, billing only on success, and automatic refund on failure or empty results. It also discloses the response shape, which matters since there is no output schema. It does not mention authentication (the _token parameter) or any rate limits.

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 compact sentences in a logical order: purpose, return fields, use cases, pricing. Each sentence contributes something and the core purpose is front-loaded. Slight redundancy between the return-field list and the use-case sentence, but nothing wasteful.

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, listing the returned fields is essential and is done here, and the pricing/refund policy completes the operational picture for a simple read-only lookup. What remains uncovered is minor for this complexity: auth mechanics and behavior on an invalid or nonexistent channel_id.

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 in the schema, including the alternate auth token and channel_id. The description adds no syntax, format, or resolution guidance for channel_id (e.g. ID vs handle), so the schema carries all parameter meaning.

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 states a specific verb and resource ("获取YouTube频道信息") and enumerates the returned fields (nickname, follower count, like count, bio, verification status), which makes it distinguishable from sibling post-search tools like yt_user_posts. It never names a sibling explicitly, so the differentiation is inferred 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?

It gives concrete usage contexts — influencer screening, account profiling, grouping by follower magnitude — so an agent knows when this tool fits. It stops short of saying when NOT to use it or which sibling to pick instead (e.g. yt_user_posts for content rather than profile data).

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