stock_hk_gxl_lg

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds the specific return content (HSI dividend yield), the return type (pandas.DataFrame), and the source URL, which is useful context but does not go into topics like data frequency or update schedule.

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 and includes only the essential return info and source URL. However, the first line duplicates the title from annotations, which adds slight redundancy.

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 zero-parameter, read-only data retrieval tool with good annotations, the description adequately explains what is returned and in what format. It doesn't describe the DataFrame's columns, but for this simple case that is acceptable.

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 this aspect. Per the baseline for 0 params, this is a 4; the description correctly avoids parameter details.

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 states that the tool returns the Hang Seng Index dividend yield (恒生指数股息率) from Legulegu, with a source URL and a pandas.DataFrame return type. It clearly identifies the resource and is distinct from other HK stock tools, though the retrieval verb is implied rather than explicit.

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 on when to use this tool versus alternatives. It simply states the data source and return value without mention of use cases, prerequisites, or exclusions.

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