macro_china_insurance

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is known. The description adds useful context by specifying the data source URL and the return type (pandas.DataFrame), but it does not disclose other behavioral traits such as data coverage, update frequency, or potential latency. With annotations doing heavy lifting, this is adequately transparent.

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 extremely concise, consisting of a source line, URL, and return type declarations. Every element serves a purpose, and it is front-loaded with the resource name. It is appropriately sized for a no-parameter data retrieval tool.

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?

The tool has no parameters and no output schema, but the description provides the source and return type. However, it does not detail the exact contents of the DataFrame (e.g., columns, units, time coverage). For a simple getter, this is acceptable but leaves ambiguity about what '保险业经营情况' specifically includes, especially given the sibling macro_china_insurance_income. More detail would improve completeness.

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?

The tool has zero parameters, and the input schema is empty with 100% coverage trivially. The baseline for no parameters is 4, and the description adds no parameter information because none exist. There is no need for additional parameter semantics.

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 clearly identifies the resource as '保险业经营情况' (insurance industry operation situation) from Sina Finance's China macro data, and specifies the return type as pandas.DataFrame. It is clear what data the tool provides, but it lacks an explicit action verb and does not differentiate from the closely related sibling tool macro_china_insurance_income.

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?

The description implies this tool is for retrieving insurance industry operating data from the Sina Finance macro dataset, but it provides no explicit guidance on when to use this tool versus alternatives, nor any exclusion criteria. The context is implied by the name and description but not stated directly.

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