stock_hk_index_daily_sina

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds only the return type (pandas.DataFrame), which is modest but real value given there is no output schema; it says nothing about the time span of '历史行情数据', frequency, or whether the full history is always returned (notably, there are no date parameters).

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 purpose is front-loaded in the first line, and the Sphinx-style lines are terse. The URL and :return:/:rtype: lines earn their place somewhat because there is no output schema, though the opening line is a verbatim duplicate of the annotation title.

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 one-parameter, no-output-schema tool the definition is minimally sufficient: an agent can call it with a default symbol and knows it gets a DataFrame. It is incomplete in that neither the valid symbol set nor the content/horizon of the returned history is described, and no sibling cross-reference is offered.

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?

Schema coverage is 0% — the single parameter has only a default of 'CES100' and no description — so the description must carry the burden. It does explain that symbol means 港股指数代码 (HK index code) and gives CES100 as the example, but it does not enumerate valid codes or the accepted format, so compensation is only partial.

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 names a specific resource (新浪财经-港股指数) and a specific output (历史行情数据), so an agent knows this returns historical HK index quotes from Sina rather than a spot snapshot. It does not, however, explicitly distinguish itself from the near-identical sibling stock_hk_index_daily_em (same data, EM source) or stock_hk_index_spot_sina, leaving that disambiguation to the tool name alone.

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?

There is no when-to-use guidance, no statement of what the tool is not for, and no reference to alternatives such as stock_hk_index_daily_em or stock_hk_index_spot_sina despite their overlapping scope. The agent must infer usage purely from the name.

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