stock_zh_index_value_csindex

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the agent knows this is a safe read operation. The description adds the return type and a source URL, but does not disclose any additional behavioral traits such as rate limits, error behavior, or what happens with invalid symbols. With annotations covering the safety profile, this is acceptable but not exceptional.

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 includes a URL, parameter documentation, and return type. Each line serves a purpose. However, the format is a somewhat fragmented docstring rather than a coherent sentence, and the URL is long. Overall, it is reasonably concise without excess verbosity.

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 simple read-only tool with one parameter and no output schema, the description provides the essential pieces: source, parameter explanation, and return type. However, it does not elaborate on what fields the valuation data contains, whether it is time-series or current, or any other expectations. Given the lack of an output schema, a bit more detail about the returned DataFrame 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 input schema provides only the parameter name and a default value, with no description. The description compensates by explaining '指数代码' (index code) and giving an example 'H30374'. Since there is only one parameter and the description clearly defines its meaning, it adds significant value beyond the schema.

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 title '中证指数-指数估值数据' clearly identifies the resource as China Securities Index valuation data. The parameter/return docstring indicates it returns a pandas DataFrame of valuation data for a given index symbol, which distinguishes it from historical price or constituent tools like stock_zh_index_hist_csindex and index_stock_cons_csindex. However, it lacks an explicit verb like 'fetch' or 'retrieve', so it reads more as a data label than a clear action statement.

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?

The description provides no guidance on when to use this tool versus alternative index-related tools. It does not mention any specific use cases, prerequisites, or situations where this tool is preferred. Sibling tools exist for historical prices, constituents, and spot data, but no exclusions or alternatives are noted.

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