macro_china_hk_market_info

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and openWorld behaviour, so safety is covered. The description adds the underlying data source URLs and the return type, which is genuinely useful context, but says nothing about refresh cadence or column contents.

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?

Short and front-loaded, leading with the dataset and its coverage. The two raw URLs add clutter but serve as the authoritative data source, and the docstring-style :return:/:rtype: is compact.

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-param, fixed-report tool with no output schema the description is mostly adequate, giving the source and return type. However a multi-field Hong Kong interbank report likely returns many columns, and the description only names 今值(%) rather than describing the DataFrame contents.

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 takes zero parameters, so there is no parameter semantics to document; a baseline 4 applies. The description correctly reflects this no-argument design.

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?

Identifies the resource precisely as the Hong Kong interbank lending report with an explicit date coverage (20170320-present), so an agent understands what dataset it returns. It does not name a verb or differentiate itself from near siblings like macro_china_shibor_all or rate_interbank, but the resource scope is 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?

Provides the effective date range as a scoping hint but gives no when-to-use guidance and never names an alternative sibling. The agent must infer from the name alone whether this or a related interbank tool is appropriate.

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