stock_institute_recommend_detail

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds that the source is Sina Finance and the return is a pandas DataFrame, but does not disclose additional behavioral traits such as pagination, rate limits, or data range.

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 structured docstring with title, source URL, parameter documentation, and return type. It is concise and easy to parse, though the URL line is somewhat extraneous.

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?

This is a simple single-parameter read-only tool. The description provides the return type (DataFrame) and what it returns (rating records). However, it lacks details about the returned columns and the exact symbol format, which could be important for correct invocation.

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?

Schema coverage is 0%, so the description must explain the parameter. It specifies 'symbol' is a stock code (股票代码) of type str, which adds meaning. However, it does not clarify whether the format requires an exchange prefix (e.g., 'sz000001' as in the URL) or just the numeric code (default '000001').

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 it returns stock rating records for a specific stock from Sina Finance's institutional recommendation pool. It uses the URL example to illustrate the data source and distinguishes itself from siblings like stock_institute_recommend by focusing on per-stock rating records.

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 alternatives. The description only documents the parameter and return type, with no mention of use cases, prerequisites, or exclusions.

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