stock_dzjy_hygtj

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the source URL and return type (pandas.DataFrame), but does not disclose other behavioral traits such as rate limits, pagination, or data freshness.

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 organized as a docstring: purpose stated first, then URL and parameter documentation. Every element is useful, though the URL is additional context rather than strictly necessary.

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 single-parameter, read-only data retrieval, the description provides sufficient information: data source, dataset name, allowed parameter values, and return type. The lack of column details in the returned DataFrame is a minor gap since no output schema is provided.

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 input schema provides no description for the 'symbol' parameter, but the description explicitly lists the four allowed values ('近一月', '近三月', '近六月', '近一年') and its type (str). This fully compensates for the schema's 0% coverage and is essential for correct invocation.

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 data source (东方财富网-数据中心-大宗交易) and the specific dataset (活跃 A 股统计), and mentions the return type (DataFrame). However, it lacks an explicit verb like 'fetch' or 'get' and does not differentiate itself from sibling block-trade statistics tools such as stock_dzjy_mrmx or stock_dzjy_sctj.

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 given on when to use this tool versus the many sibling block-trade tools. There are no stated prerequisites, conditions, or exclusions, leaving the agent to infer usage solely from the dataset name.

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