stock_lhb_stock_detail_date_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 the safety profile is clear. The description adds minimal extra context (source URL, return type as DataFrame) but does not disclose behaviors like date handling, error cases, or data scope. Since annotations cover the core aspects, a score of 3 is appropriate.

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 short and to the point, but it is poorly structured for an agent. It repeats the title, then provides a URL and docstring. There is no front-loaded purpose sentence, and the format is more like a raw function docstring than a clear tool description. It is not overly verbose, but it sacrifices clarity for brevity.

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 tool name includes 'date' but the input schema only has 'symbol' with no date parameter. The description does not explain how the date is determined or whether the tool returns data for a specific date. There is no output schema, so the return structure is unknown. Given the ambiguity and missing context, the description is incomplete.

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 one parameter (symbol) with no description (0% coverage). The description only states '股票代码' (stock code), which is redundant with the parameter name. It does not explain the expected format (e.g., leading zeros, exchange prefix), provide examples, or clarify how the symbol relates to the 'date' aspect of the tool. This is insufficient compensation for the missing schema description.

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 is essentially a label: '东方财富网-数据中心-龙虎榜单-个股龙虎榜详情-日期' (East Money, Dragon Tiger List, Individual Stock Detail, Date). It lacks a clear verb or explicit statement of what the tool does (e.g., 'fetches the historical LHB detail for a given stock'). The title is repeated but adds no functional clarity, and it does not differentiate from sibling tools like stock_lhb_stock_detail_em.

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?

No guidance is provided on when to use this tool versus alternatives. There is no mention of scenarios, prerequisites, or exclusions. The URL and param are given but no context on how this fits into a workflow or why one would choose this over other LHB-related tools.

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