macro_australia_cpi_yearly

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds the return type (pandas.DataFrame) and the data source URL, which is useful. However, it doesn't describe the DataFrame's columns, frequency, or any potential network dependencies, leaving some behavioral ambiguity.

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 extremely concise, with each line serving a purpose: title, source URL, return value, and return type. It is well-structured and front-loaded, with no wasted words.

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, the description provides the essential information: the data source, the specific economic indicator, and the return type. However, without an output schema, it would benefit from describing the DataFrame's structure (e.g., columns) and historical range, which is absent. Still, it is adequate for invoking the 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 there is nothing for the description to clarify. The input schema is empty and sufficient. Per the rubric, 0 parameters gets a baseline of 4.

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 retrieving Australia's Consumer Price Index yearly rate from Eastmoney, including a source URL. It distinguishes from sibling tools like macro_australia_cpi_quarterly by the 'yearly' qualifier in both the name and description. However, it lacks an explicit verb (e.g., 'get', 'fetch'), so it reads more as a title than a directive.

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 offers no guidance on when to use this tool versus alternatives. It doesn't mention any conditions, exclusions, or related tools. The only context is the indicator name itself, which is insufficient given the large number of sibling macro tools.

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