macro_japan_bank_rate

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds minimal behavioral context—only that the return type is pandas.DataFrame. It does not mention any pagination, rate limits, or data completeness, but for a simple read-only data retrieval with no parameters, this is acceptable.

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 very short and to the point, containing only the source label, URL, and return type. However, the formatting is somewhat unstructured with the URL embedded, and the ':return:' line redundantly repeats the title. Despite this, every part adds some information and there is no wasted prose.

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 tool with no parameters and no output schema, the description should at least clarify what the returned DataFrame contains. It only says '央行公布利率决议' (central bank interest rate decision), which is vague about columns, historical coverage, or data structure. The low complexity makes this minimally viable, but more detail would help an agent understand the exact data returned.

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 carries full coverage (100%). The description does not need to explain parameters, and it doesn't. The baseline of 4 for zero-parameter tools applies, and the description's mention of the return type adds a small but useful detail.

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 providing Japan's central bank interest rate decisions from Eastmoney economic data, with a specific source URL. While it lacks an explicit verb like 'get' or 'returns', the title and context make the purpose unambiguous. It does not explicitly differentiate from similar sibling tools like macro_bank_japan_interest_rate, but the specific data source and wording make its scope clear.

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?

No guidance is provided on when to use this tool versus alternatives. The many sibling tools, including macro_bank_japan_interest_rate and other Japan macro indicators, make this a significant gap. A sentence indicating that this tool is for interest rate decision announcements rather than current rate levels would be valuable.

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