macro_china_cpi_yearly

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

The description adds useful behavioral context beyond annotations: the date range, a source URL, and the pandas.DataFrame return type. However, it does not disclose specifics like whether the data represents year-over-year percentage change, column names, or update frequency, so transparency is partial.

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 compact and front-loaded with the key information (annual CPI and date range). The URL and :return/:rtype docstring lines are useful but slightly redundant with the title and name, yet the overall structure is clean and not verbose.

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 tool with 0 parameters, good safety annotations, and no output schema, the description covers the basics: what data (annual CPI), the time span, and the return type. However, it omits important context such as the exact units (year-over-year percentage), column names, or the fact that it is historical annual data, leaving the agent uncertain about the data's semantic meaning.

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 schema coverage is 100% with an empty schema. The baseline for 0-parameter tools is 4, and the description does not need to explain parameter semantics, though it does mention the date range as a property of the data.

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 China annual CPI data with a specific date range (19860201 to present), which distinguishes it from monthly or other CPI-related siblings. However, it lacks an explicit verb like 'retrieve' or 'list,' relying on the noun phrase '中国年度 CPI 数据' to imply action.

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 such as macro_china_cpi_monthly or other CPI tools. It does not mention exclusions, prerequisites, or contextual cues for selection, leaving the agent without decision-support information.

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