fund_hk_rank_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds the source URL and return type but does not disclose any additional behavioral traits such as data update frequency, pagination, or network dependencies. No contradiction 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 extremely concise, containing only the title, URL, return value, and return type. Every line serves a purpose with no fluff, and the key information is front-loaded.

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 description provides minimal context: it states the data source and that it returns a DataFrame of Hong Kong fund rankings, but does not describe the columns, ranking criteria, or whether it returns a full list. For an agent to fully utilize the output, more detail would be helpful, but the basic function is clear.

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 an empty schema, so the description does not need to explain parameter semantics. According to the baseline for 0-parameter tools, this scores 4; there is nothing missing in this dimension.

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 Hong Kong fund rankings from East Money's data center, including the source URL and return type (pandas.DataFrame). It distinguishes from sibling tools by specifying Hong Kong funds, though it lacks an explicit action verb like 'retrieve' or 'list'.

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 intended usage is implied by the name and description: use when Hong Kong fund rankings are needed. However, there is no explicit guidance on when to use this tool versus other fund ranking tools (e.g., fund_open_fund_rank_em, fund_exchange_rank_em), and no alternatives are mentioned.

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