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

The annotations already declare readOnly, idempotent, openWorld, and non-destructive, so the safety profile is covered. The description adds genuinely new behavior: results are in reverse chronological order, each item contains an ID plus engagement metrics, and there is a per-call price of ¥0.3 that is billed only on success with automatic refunds for failures or empty results. These cost and billing semantics are exactly the kind of detail annotations cannot convey.

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 short sentences with zero padding. The purpose is front-loaded, followed by the return shape, use cases, and billing. Each sentence adds distinct information an agent needs.

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?

Because there is no output schema, the description's brief summary of return values ('content ID plus basic engagement data', reverse chronological) is essential and present, and pricing is disclosed. The one gap is pagination: how last_buffer works, roughly how many items per page, and whether an empty cursor means the end of the list are left unstated.

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%, so username, last_buffer, and _token are already documented in the schema. The description adds nothing about the pagination cursor's usage or how the reverse-chronological ordering interacts with last_buffer, so the schema does the heavy lifting here, making 3 the correct baseline.

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 opens with a specific verb + resource: 获取视频号账号作品列表, and clarifies that this returns the list of content published by the account, including per-item IDs and basic engagement data. That makes it clearly different from channels_post_detail (single item details) and channels_user_info (account metadata), but it never explicitly contrasts itself with channels_search_in_channel, the closest sibling.

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 names concrete use cases: monitoring account posting frequency, analyzing content strategy, or batch-fetching content IDs. That gives the agent a clear 'when to use' signal. It stops short of naming an alternative tool or a 'when not to use' condition, so it falls just below the top score.

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