macro_uk_cpi_yearly

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is covered. The description adds the return type (pandas.DataFrame) and source URL, but does not disclose data granularity, columns, update frequency, or any caveats about the scraping source. This is modest added 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 very concise, with a title line, URL, and return docstring. It wastes no words and is front-loaded with key identifying information. However, the structure reads more like a code comment than a coherent narrative, which slightly reduces clarity.

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 zero-parameter read-only tool, the description provides essential identification and return type, which is minimally adequate. However, without an output schema, it does not describe the DataFrame's columns, time range, units, or other details, leaving an agent uncertain about the exact output format beyond the indicator name.

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 fully self-descriptive (100% coverage). The description confirms the return type but adds no parameter semantics, which is appropriate and consistent with the baseline for parameterless tools.

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 explicitly identifies the source (Eastmoney/东方财富), country (UK/英国), and indicator (CPI yearly rate/消费者物价指数年率), with a URL for the data page. This clearly distinguishes it from siblings like macro_uk_cpi_monthly or macro_uk_core_cpi_yearly, though it lacks an explicit verb such as 'get' or 'return', making it more of a label than a complete sentence.

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?

There is no guidance on when to use this tool versus alternatives. The description does not mention related tools like macro_uk_cpi_monthly or macro_uk_core_cpi_yearly, nor does it provide selection criteria. The only implicit signal is the tool's name and the indicator label.

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