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

The description adds useful behavioral context beyond the raw schema: it is billed by usage, and the invocation returns a result, order number, and remaining balance. However, with no annotations provided, it does not go far enough to disclose possible side effects when calling a 'tool' asset, authentication requirements, failure modes, or cost 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?

The description is a single, efficient sentence with no filler and front- loads the most important information: what the tool invokes, that it is metered, and what it returns. It is not overly long, but it also doesn't use any paragraph or bullet structure to help with longer usage guidance.

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?

For a tool with five parameters, no annotations, and no output schema, the description still gives a helpful one-line summary of the return values (result, order number, balance). Yet it leaves out important context like what happens for tool-type assets, whether the call is async, and what error or cost-related details are returned.

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 all five parameters already have meaningful descriptions in the input schema. The tool description does not add any additional semantic detail about parameters, so the baseline 3 is appropriate.

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 uses a specific verb ('调用') and a specific resource ('AI 资产'), and clarifies the two possible variants: LLM conversation or tool. It clearly distinguishes itself from list_assets/get_onboarding/bootstrap_account by saying it actually invokes the asset and bills for it, though it does not explicitly state how it differs from ai_estimate.

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?

There is no explicit guidance on when to use this tool versus its sibling ai_estimate or list_assets. The description says what the tool does, but it never states the prerequisite workflow ('get asset_id from list_assets first') nor that ai_estimate should be used for cost estimation before a request.

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