macro_china_trade_balance

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

Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds useful context beyond annotations: the data range (19810201-now), source URLs, and return type (pandas.DataFrame). It does not contradict any annotations and provides additional non-obvious information about the data source.

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 relatively concise and front-loaded with the core meaning. It includes source URLs and return type in a structured format. The URLs add some clutter but are not excessive. The sentences are short and every part has a purpose (definition, source, output type).

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 has no parameters and no output schema, the description provides essential context: data range, source, and return type. However, it does not specify the data frequency (e.g., monthly, yearly), column names, or any caveats about the data (e.g., seasonality, adjustments). This makes it minimally complete but with notable gaps for an agent that needs to interpret the returned DataFrame.

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?

With zero parameters, the schema provides no parameter descriptions, so the description does not need to explain parameter semantics. The baseline for 0 params is 4, and the description adds context about the return type and data range, which is sufficient. There is no missing parameter information to compensate for.

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 it provides China's trade balance in USD with a specific date range (19810201-present). It distinguishes itself from sibling tools like macro_usa_trade_balance or macro_uk_trade by explicitly mentioning China and USD. However, it lacks an explicit verb (e.g., 'get', 'retrieve'), so it reads more as a noun phrase than an action description.

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 only states what it returns, with no mention of suitable scenarios, prerequisites, or exclusions. Unlike the calibration high example, it doesn't name alternative tools or provide decision criteria.

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