macro_bank_newzealand_interest_rate

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds that the data range starts from 19990401 and that the return is a pandas Series of current values in percent, plus source URLs. It doesn't contradict annotations and provides useful context about the output.

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 a single sentence with core info and URLs, no redundancy. It's front-loaded with the main idea.

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 no-parameter read-only tool, the description covers the essential aspects: what data, range, return type, and source. It doesn't mention language or potential data updates, but that's minor.

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 fully covers them (100% coverage). The baseline for zero parameters is 4; the description additionally clarifies the return format but no parameter syntax is needed.

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 tool provides the New Zealand Federal Reserve (RBNZ) interest rate decision report, covering data from 19990401 to present, returning the current value in percent as a pandas Series. The tool name and description align, but it doesn't explicitly differentiate it from sibling macro_bank_* tools.

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 other central bank interest rate tools (e.g., macro_bank_australia_interest_rate). No alternatives, exclusions, or prerequisites are mentioned.

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