stock_lhb_stock_detail_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds meaningful behavioral context beyond these by disclosing the dependency on another function to get valid dates and specifying the return type as pandas.DataFrame. No contradictions 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 compact and well-structured: title, URL, then clearly labeled param and return sections. Every sentence adds value, and there is no redundant or filler content. It is appropriately front-loaded with the tool's purpose.

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 tool with no output schema, the description covers the essential usage: the data source, the prerequisite date function, allowed flag values, and the return type. It falls slightly short by not describing the actual columns or contents of the returned DataFrame under '个股龙虎榜详情', which could help an agent understand the data structure, but overall it is sufficiently complete for invocation.

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 description coverage is 0%, so the description carries the full burden for parameter meaning. It explains all three parameters: symbol (股票代码), date (with the critical prerequisite of calling the date tool), and flag (explicit allowed values '买入' and '卖出'). It also provides a date format hint via the default value '20220315'.

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 fetching individual stock Dragon-Tiger List details from Eastmoney's data center, with the URL example showing the exact page. It distinguishes itself from siblings via '个股' (individual stock) and the specific parameters, making its purpose unambiguous even without an explicit verb.

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 a clear usage context by stating that the date parameter must be obtained from the prerequisite function stock_lhb_stock_detail_date_em. It implicitly tells the agent how to use the tool correctly, though it does not explicitly mention when not to use it or contrast with alternatives.

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