macro_japan_unemployment_rate

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the data source (East Money URL) and return type (pandas.DataFrame), which provides some extra context beyond annotations. However, it doesn't disclose data frequency, coverage limitations, or potential missing values, so transparency is adequate but not rich.

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 concise, containing only the essential elements: the data source, URL, return value, and return type. Every line serves a purpose. It's slightly unstructured due to the raw docstring format, but it's appropriately sized for a simple, parameterless 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?

For a zero-parameter tool with no output schema, the description provides enough context: it states the data source, what is returned (unemployment rate), and the return type (DataFrame). It doesn't specify historical range or update frequency, but the low complexity and clear naming make the tool usable. Slight gaps exist, such as column details, but these aren't critical for the tool's basic function.

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?

There are zero parameters, so schema coverage is 100% by default. The description doesn't need to explain parameter details. The baseline for 0 parameters is 4, and the description correctly omits any parameter information, as there is nothing to clarify.

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 states the resource: East Money economic data for Japan's unemployment rate (东方财富-经济数据-日本-失业率). It includes a source URL and return type, making it distinct from sibling tools for other countries' unemployment rates. The verb is implied (retrieve/get), but the intent is unambiguous.

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 implies use when Japan's unemployment rate is needed, and the name distinguishes it from other country-specific tools. However, it provides no explicit guidance on when to choose this tool over alternatives, and doesn't mention any exclusions or prerequisites. Usage is inferred rather than stated.

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