stock_index_pb_lg

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description need not repeat safety details. It adds a source URL and return type (pandas.DataFrame), but does not describe the DataFrame's columns, historical depth, or any pagination or rate-limit characteristics. This is partial but not comprehensive context.

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 a title, URL, and a standard docstring structure. It includes only relevant information without padding. Slight redundancy exists because the title repeats the Chinese name, but overall it is well-structured and easy to scan.

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?

With no output schema, the description should clarify what the returned DataFrame contains. It only says '市净率数据' (PB data) and the type, which is minimal. It also lacks any note on historical range or data granularity. Given the simple one-parameter nature, the description covers the basics but leaves important details unstated.

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 only provides a string parameter with a default and no description (0% coverage). The description compensates by fully listing the valid symbol choices ({{"上证50", "沪深300", ...}) and the type (str), which is essential for correct invocation. It does not explain the meaning of each index, but the list itself is sufficient for selection.

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 indicates the tool provides PB (price-to-book) data for specified stock indices via the title '乐咕乐股-指数市净率' and the return statement '指定指数的市净率数据'. It specifies a resource (index PB) and a limited set of supported indices, distinguishing it from generic market PB tools, though it lacks an explicit verb like 'get' or 'retrieve'.

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. It does not mention sibling tools such as stock_market_pb_lg or stock_index_pe_lg, and provides no exclusions or prerequisites. The intended use is only implied by the specific index list, but an agent would have to infer when this is the right tool.

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