macro_usa_core_pce_price

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds context by specifying the data range (19700101-至今), the data source URL, and the return type (pandas.DataFrame). It does not disclose update frequency, exact columns, or any rate limits, but given the strong annotations, this is acceptable.

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 short and front-loaded with the key resource name. It includes a source URL and return type, which are useful. However, it repeats the report name in the ':return:' line and the title duplicates the description's first sentence, adding minor redundancy.

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 simple parameterless read-only indicator, the description provides the essential context: what data is returned, the time span, and the source. No output schema exists, but the return type is stated. It lacks explicit periodicity (e.g., monthly vs annual), though '年率' implies yearly rate. Overall, adequate for selecting and invoking the tool.

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?

There are zero parameters, and schema coverage is 100% (since no properties are defined). The description does not need to explain parameters, and the baseline of 4 is appropriate for a parameterless tool. It correctly returns a DataFrame without requiring any input.

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 the tool provides the US Core PCE Price Index Year-over-Year report, with data range from 19700101 to present. The name 'macro_usa_core_pce_price' aligns with this, and it is distinguishable from sibling macro tools like CPI or PPI. However, it lacks an explicit verb like 'get' or 'list', relying on the noun '报告' (report), which slightly reduces clarity.

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?

No guidance is given on when to use this tool versus alternatives. The description merely describes the report and provides a source URL. It does not mention exclusions, prerequisites, or alternative tools for similar economic indicators, leaving the agent to infer usage from the name alone.

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