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

Annotations already declare this as read-only, idempotent, non-destructive, and open-world, so safety is covered. The description does add real behavioral value beyond that: per-call pricing of ¥0.3, billing only on success, and automatic refunds for failures or empty results. The gap is that it never explains the relationship between object_id and share_url, and never says whether either is required.

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, front-loaded with purpose, then return values, then use cases, then billing. Every sentence carries information (the billing terms are not filler for a paid API), though the return-field list is the least actionable line.

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, describing the returned fields is necessary and useful. But the definition is still incomplete for a 3-parameter tool with zero required fields: it doesn't say which identifier to supply or what to do about the _token fallback versus the header, leaving the agent to guess at invocation semantics.

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 the baseline is 3. The description adds no parameter guidance, and it is silent on the important ambiguity that no parameter is marked required but a post presumably needs either object_id or share_url, and on how a share link should be resolved.

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 ("获取微信视频号作品详情") and enumerates what is returned (作品描述、点赞/评论/转发数、账号信息、发布时间), which clearly separates it from the aggregate channels_user_posts or channels_search_in_channel siblings. However, it never names a sibling tool, so the differentiation is implicit rather than explicit.

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 when-to-use contexts: single-item engagement analysis, asset archiving, or as the entry point for a batch job. That's good positive guidance, but there are no exclusions, prerequisites, or named alternatives for when a search or user-post listing would be better.

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