fund_etf_dividend_sina

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds that the data comes from Sina Finance and returns a pandas.DataFrame, plus a reference URL. However, it does not disclose any behavioral details such as data frequency, pagination, or limitations. Given the annotations cover the safety profile, adding the source and return type provides marginal extra value, but not enough to score higher.

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 relatively short, but its structure is a jumble: a title line, an unformatted URL, and a docstring-style param/return block. It lacks a clear opening sentence with a verb. The URL is arguably redundant for an agent. While no part is wastefully verbose, the lack of coherent structure and front-loading prevents a higher score.

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?

With no output schema, the description carries the burden of explaining the return value. It only says '累计分红' (cumulative dividends) and 'pandas.DataFrame', which essentially repeats the title. It does not describe the columns, the meaning of 'cumulative', or whether the data covers the full dividend history. For an agent to confidently use the tool, more detail is needed, so this is minimally complete.

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 schema has only one parameter 'symbol' with no description, so schema coverage is 0%. The description attempts to explain it as '基金名称' (fund name) and says it can be obtained via ak.fund_etf_category_sina(). This is partially helpful for finding valid values, but 'fund name' is misleading; the default 'sh510050' is an exchange symbol, not a name. The description does not fully clarify the expected format (e.g., prefix 'sh'/'sz'), leaving the agent with an inaccurate mental model.

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 begins with '新浪财经-基金-ETF 基金-累计分红' which clearly identifies the resource as cumulative dividends for ETF funds from Sina Finance. Although it is a title rather than a full sentence with a verb, the intent is unambiguous and distinguishes this tool from sibling tools like fund_etf_hist_sina (historical prices) and fund_etf_spot_em (spot quotes). The URL and return type further reinforce the purpose.

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 gives no explicit guidance on when to use this tool versus alternatives. It only mentions how to obtain the symbol via ak.fund_etf_category_sina() as a prerequisite, but does not explain when to choose this dividend tool over other fund-related tools (e.g., fund_announcement_dividend_em). There are no exclusions or comparisons to siblings, leaving the agent to infer usage from the name and title.

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