macro_usa_core_ppi

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering safety. The description adds meaningful behavioral context: the data range, the return type (pandas.DataFrame), and that it returns the current value in percent. This is beyond what annotations provide and helps the agent understand output expectations.

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 concise, front-loading the core purpose and data range, followed by a source URL and return type. It is not overly verbose, but the inclusion of a URL and docstring-style return info slightly disrupts a clean structure. All sentences contribute relevant information.

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 zero parameters and no output schema, the description is relatively complete. It specifies the data source, time coverage, return type, and the unit of the value. It does not enumerate DataFrame columns, but for a simple macro data retrieval that may be acceptable. The lack of alternatives or caveats is a minor gap.

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, so the baseline score is 4. The description effectively communicates what the tool returns (current PPI value in %) and its output format, which is sufficient for a parameterless tool.

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 provides the US Core Producer Price Index (PPI) report with a specific data range (20080318-至今). The resource and scope are explicit, and the name distinguishes it from related tools like macro_usa_ppi. However, it lacks an explicit verb like 'get' or 'return' and does not explicitly call out differentiation from siblings.

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 explicit guidance on when to use this tool versus alternatives. The description only mentions the data range, which implicitly suggests it is for historical data, but it does not mention related tools (e.g., macro_usa_ppi) or provide exclusions. An agent would need to infer usage from the tool name and context.

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