macro_bank_india_interest_rate

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, covering safety. The description adds valuable context: the data range from 20000801 to the present, source URLs, and the return type. No contradictions with annotations.

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, containing the key purpose, data range, source links, and return type. It is structured like a docstring, though the URLs add some clutter. It earns its place without excess.

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 simple zero-parameter read-only tool, the description is complete: it specifies what data is returned, the time period, and the return format (pandas.Series). No output schema exists, so the explicit return type is helpful.

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 the baseline is 4. The description does not need to add parameter meaning, and the schema coverage is effectively 100% with no parameters to document.

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 '印度利率决议报告' (India interest rate decision report) and specifies the data range and return type. It distinguishes from sibling tools by explicitly naming India and providing the return value format (今值/current value in %).

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 its use for India interest rate data with the date range and source links, but it does not explicitly state when to use it over alternatives like other macro_bank_* tools. No exclusions or alternative tool references are provided.

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