stock_index_pe_lg

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds only the source URL and the list of valid symbols, but does not disclose behavioral traits such as whether data is historical or current, data granularity, or any rate limits or authentication requirements. It goes barely beyond the annotations.

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 a compact docstring with a title, source URL, parameter specification, and return type. It is front-loaded with the title, and every line is informative without unnecessary verbosity. The structure is clean and easy to parse.

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 tool with no output schema, the description adequately covers purpose, input choices, and return type. It lacks details about the exact contents of the returned DataFrame (e.g., columns, time range), but given the tool's simplicity and the provided annotations, it is reasonably complete.

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 schema has a single parameter 'symbol' with no description and no enum, but the description provides a complete enumeration of accepted values: 上证50, 沪深300, 上证380, etc. This is critical for correct usage and fully compensates for the 0% schema description coverage.

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 states the tool retrieves index PE ratio data from Legulegu ('乐咕乐股-指数市盈率') and documents the return as '指定指数的市盈率数据' (PE data for the specified index). This distinguishes it from sibling tools like stock_index_pb_lg (PB ratio) and stock_market_pe_lg, as it focuses specifically on index PE.

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 implies usage for fetching PE data for one of the listed Chinese indices, but it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or alternative tools. The usage context is clear from the title and return description, but not explicitly articulated.

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