get_macro_employment

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

Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds value by specifying the exact data points (non-farm payrolls, unemployment rate, etc.) and explaining the impact on Fed interest rate expectations, which provides useful behavioral context beyond annotations.

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 at two sentences, covering both the data provided and its significance. Every sentence is meaningful and front-loaded.

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?

Given no parameters and no output schema, the description adequately explains what data is retrieved and why it matters. Minor gap: the format of the output is unspecified, but for a simple read tool this is acceptable.

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 no parameters, so schema coverage is effectively 100%. The description does not need to add parameter information. According to calibration guidelines, 0 parameters warrants a baseline score of 4.

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 states the tool retrieves US employment market data including specific metrics (non-farm payrolls, unemployment rate, labor participation rate, trends). The verb '取得' (get) and resource are explicit, and the tool is well-distinguished from siblings like get_macro_inflation.

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 usage for employment data related to Fed policy but does not provide explicit guidance on when to use this tool versus alternatives such as get_macro_snapshot or get_macro_series. No when-not or alternative naming is given.

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