获取CPI通胀数据

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

With no annotations, the description carries the full burden. It discloses data granularity (monthly) and included metrics (YoY, MoM), which is useful. However, it does not describe the return format, data source, rounding, or any behavioral quirks, so transparency is moderate.

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?

Description is a single, front-loaded sentence that efficiently conveys the tool's purpose and data content without waste. Each phrase carries meaning, and it is appropriately sized for the tool's simplicity.

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 is simple (one parameter, no output schema, no annotations), the description covers core functionality but lacks detail on output shape, time range behavior, and source. This leaves an agent relying on assumptions for return values.

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 schema already describes the single 'limit' parameter with a type and suggested range (12-60). The description adds no additional meaning for the parameter, so it stays at the baseline for full 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?

Description clearly states the tool retrieves China's monthly CPI data, including YoY and MoM rates, using a specific verb (获取) and resource (中国CPI月度数据). This distinguishes it from sibling macro tools like GDP or PMI, though it does not explicitly name alternatives.

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 a clear usage context ('用于分析通胀水平' – for analyzing inflation), signaling when to use this tool. However, it does not explicitly state when not to use it or mention alternative tools, so it stops short of full exclusions.

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