xincaifu_rank

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

Annotations already declare the operation as read-only, idempotent, and non-destructive. The description adds the source URL and the year range (2003-present), plus a return type of pandas.DataFrame. However, it does not disclose behavior for invalid years, the nature of the ranking data, or any potential errors. Given the annotation coverage, the description provides modest additional context but not rich behavioral detail.

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 compact and follows a docstring-like structure with a title, source URL, parameter documentation, and return type. It avoids unnecessary verbosity and packs essential information into a few lines. The URL is a bit of clutter but provides the data source, making it useful overall.

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 simple tool with one parameter, it provides essential information: source, parameter range, and return type. However, without an output schema, the return value is only described as '排行榜' (ranking list) and pandas.DataFrame, which leaves ambiguity about the specific columns or data details. It is adequate but has clear gaps in fully specifying what is 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 input schema has 0% description coverage for the 'year' parameter, but the description includes ':param year: 具体排名年份, 数据从 2003-至今', which clarifies that year is a string representing the ranking year and provides a valid range. This compensates for the schema's lack of description. It could be more explicit about the expected format (e.g., 'YYYY'), hence not a 5.

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 identifies the tool as the '新财富 500 人富豪榜' and includes a source URL, clearly indicating it retrieves the New Fortune 500 Richest ranking. It distinguishes from sibling tools like forbes_rank and hurun_rank by naming the specific source '新财富', but it lacks an explicit action verb like 'get' or 'fetch'.

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 description provides no guidance on when to use this tool versus alternatives. It does not mention when to choose this over forbes_rank or hurun_rank, nor does it state any exclusions or prerequisites. The only contextual clue is the data range '2003-至今', which is parameter information rather than usage guidance.

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