macro_usa_cpi_yoy

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the data range (2008-present) and source URL, plus the return type (pandas.DataFrame), but does not disclose details like available columns, data frequency, or potential missing values. This is moderate value 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 relatively brief, front-loading the key identifier (source and metric) and including a helpful URL and return type. The docstring-style ':return' and ':rtype' lines are slightly redundant but not harmful. It is efficient and well-structured for a simple 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?

Given the tool's simplicity (no parameters), strong annotations, and lack of an output schema, the description provides adequate context: it names the exact economic indicator, data source, date range, and return type. It could be improved by listing typical columns, but that is not critical for a straightforward read-only data retrieval 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?

The tool has zero parameters, so the schema is trivially complete. Per the baseline for 0 params, this dimension scores 4. The description does not need to add parameter semantics since none exist, and the description confirms no inputs are required.

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 providing US CPI year-over-year data from East Money, with an explicit data range (2008-present). It distinguishes from sibling tools like macro_usa_cpi_monthly by specifying '年率' (annual rate), though it lacks a direct action verb like 'retrieve' or 'fetch'.

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 provides no guidance on when to use this tool versus alternatives (e.g., macro_usa_cpi_monthly or macro_usa_core_cpi_*). It implies usage for US CPI YoY data but does not state exclusions or alternatives, leaving the agent to infer from the name and description alone.

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