stock_lhb_hyyyb_em

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

Annotations already convey readOnly, openWorld, idempotent, and non-destructive behavior. The description adds the return type (pandas.DataFrame) and the source URL, which is useful context beyond annotations, but it does not disclose any additional behavioral traits such as pagination, rate limits, or date range constraints.

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 concise and follows a clear docstring structure with source URL, params, and return type. It is appropriately sized with no fluff, though the first line duplicates the title annotation.

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 two-parameter read-only data retrieval tool with strong annotations, the description is minimally adequate. It provides source, return type, and parameter names, but lacks usage context and explicit date format guidance. It is not as rich as tools with detailed behavioral or situational context.

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 must explain the parameters, but it only restates the names in Chinese ('开始日期', '结束日期') without specifying format, requiredness, or constraints. The defaults show YYYYMMDD format, but this is not explicitly stated in the description, leaving the agent to infer.

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 specific data resource: '东方财富网-数据中心-龙虎榜单-每日活跃营业部' (East Money Data Center - Dragon Tiger List - Daily Active Business Departments), and the return type 'pandas.DataFrame' clarifies it retrieves this data. It distinguishes from sibling tools like stock_lhb_yybph_em or stock_lhb_yyb_detail_em by naming the specific daily active department scope, though it lacks an explicit verb like 'get' or 'list'.

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, nor are any prerequisites or exclusions mentioned. The description only states what the data is, not the context in which an agent should select it.

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