macro_usa_cpi_monthly

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

The annotations already declare the tool as read-only, non-destructive, and idempotent. The description adds useful context about the data range (since 1970) and the return type (pandas.DataFrame), plus a source URL. However, it doesn't disclose details about the DataFrame's contents, columns, or potential time zones, so it adds limited behavioral context.

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 appropriately compact, with the key information front-loaded. Slight redundancy exists in repeating the report name in the :return: line, but overall it's concise.

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 data retrieval tool with no parameters, the description provides the essential scope (data range) and return type. However, it lacks details about the DataFrame's structure, such as columns or the meaning of '月率', which could matter for an agent deciding on data extraction.

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, so there are no parameter semantics to clarify. The baseline of 4 applies, and the description doesn't need to compensate for a low schema coverage.

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 tool as a US CPI monthly rate report with a specified data range and a source URL. It's specific about the resource and frequency, though it doesn't explicitly differentiate from related CPI tools like core CPI or YoY variants beyond the name.

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 usage guidance is provided. The description doesn't mention when to use this tool versus alternatives like macro_usa_cpi_yoy or macro_usa_core_cpi_monthly, nor does it specify any prerequisites or context.

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