macro_bank_brazil_interest_rate

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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds useful context beyond annotations: the exact date range, source URLs, return type (pandas.Series), and current value unit (%). This helps set expectations for the output and data provenance.

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 brief and front-loaded with the core purpose and date range. It also includes source URLs and return documentation, which adds some clutter but is still concise and information-dense. No unnecessary fluff.

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 simplicity of the tool (no parameters, read-only, clear data source), the description is complete enough for an agent to select and invoke it correctly. It specifies the data range, source, and output format. The lack of an output schema is mitigated by the explicit return type and unit.

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 are no parameter semantics to explain. The description provides return type and value details, which compensates for the lack of an output schema. A baseline of 4 is appropriate for a no-parameter tool.

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 a Brazil interest rate decision report with a specific date range (20080201 to present). It is distinguishable from sibling macro_bank_* tools by the country in its name, but it lacks an explicit verb like 'get' or 'fetch'. The purpose is nonetheless 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 usage for retrieving Brazil's interest rate decision data but does not explicitly state when to use this tool versus alternatives. Given the clear country-specific name and the structure of sibling tools, an agent can infer when it is appropriate, but no direct comparison or exclusion is provided.

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