stock_info_sh_name_code

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

The annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, covering the safety profile. The description adds the specific symbol choices and the fact that it returns a pandas DataFrame, but does not disclose further behavioral traits such as rate limits or the meaning of the return data. No contradiction with annotations exists.

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 front-loaded with the title and URL. However, it includes a confusing return line '指定 indicator 的数据' which appears to be a template artifact and adds noise. Overall, it is appropriately compact for a simple tool but not perfectly clean.

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 is simple with one optional parameter and no output schema. The description provides the parameter choices and return type, but does not explicitly describe the DataFrame contents (e.g., stock code and name), and the return line is ambiguous. Given the name suggests 'name_code', a more explicit mention of the output columns would improve completeness. Still, the essentials are present, so it is minimally adequate.

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 has 0% description coverage and no enum values. The description compensates by listing the allowed symbol values: '主板A股', '主板B股', '科创板' with their corresponding codes, and specifying the type as str. This gives the agent the necessary semantic information to choose the correct parameter value.

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 provides the title '上海证券交易所-股票列表' (Shanghai Stock Exchange Stock List) and a source URL, clearly indicating this tool fetches the SSE stock list. The verb is implicit rather than explicit (e.g., 'get' or 'fetch'), and it does not clearly distinguish from sibling tools like stock_info_a_code_name or stock_info_sz_name_code, though the exchange is named. Thus it is clear but lacks explicit sibling differentiation.

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?

There is no guidance on when to use this tool versus alternatives. The description only lists parameter choices and a return type, with no mention of suitable use cases, exclusions, or references to sibling tools. This is 'no guidance' per the rubric.

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