macro_china_hk_building_amount

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds that the return is a pandas.DataFrame and provides a source URL, which is some useful context. However, it does not disclose details like data frequency, date range, or column structure, so it remains at a baseline level.

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 short but somewhat redundant: the title is repeated in the annotation, and the ':return:' line essentially restates the title. The URL is useful but the structure is not optimized. It is not as lean as a two-sentence description that adds distinct value.

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?

The tool is simple with no parameters, but there is no output schema. The description only gives a generic label and return type, without explaining what columns, time periods, units, or ranges are included. This is insufficient for an agent to understand what data will be returned and how it might be used.

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, and the schema is empty. With no parameters to document, a baseline of 4 applies. The description does not need to explain parameter semantics because there are none.

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 specific resource: Hong Kong building sale contract transaction amounts from East Money, with a source URL. It implies retrieval and the return type is stated as pandas.DataFrame. While there is no explicit verb like 'get' or 'fetch', the resource and scope are clear, and the name distinguishes it from the sibling macro_china_hk_building_volume.

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 given about when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or context in which this data would be preferable. The description is purely declarative and leaves the agent to infer usage from the name.

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