stock_zh_a_new_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds the source URL and return type (pandas DataFrame), but no additional behavioral traits like rate limits, pagination, or network dependencies. Since annotations cover the safety profile, a 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 compact, with three useful lines: source/scope, URL, and return type. The URL might be extra but provides context. It is not padded or verbose, earning a 4.

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 no-parameter tool without an output schema, the description conveys the basic purpose and return type. However, it does not detail what 'new stocks' means (e.g., listing time window), the columns in the DataFrame, or any other constraints. Given the many sibling stock tools, a bit more explanation of the exact data would improve completeness.

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 tool has zero parameters, so no parameter information is needed. According to the rubric, 0 parameters gives a baseline of 4. The description correctly provides no unnecessary parameter details.

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 data source (东方财富网/行情中心/沪深个股/新股) and the output (新股, pandas DataFrame). The verb is implicit rather than explicit, but the resource and scope are clear. The mention of Eastmoney and URL helps distinguish from siblings like 'stock_zh_a_new'.

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 similar siblings (e.g., 'stock_new_a_spot_em', 'stock_zh_a_spot_em'). There is no comparison, prerequisites, or alternative recommendations, making it purely a data-source docstring.

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