stock_fhps_detail_ths

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds the data source URL and return type (DataFrame) but doesn't disclose edge cases, error behavior, or data fields. It adequately communicates a safe read operation without adding significant new behavioral detail.

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, uses clear docstring conventions, and has no wasted words. It front-loads the purpose and includes essential parameter and return info.

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, the description covers the basic purpose, parameter, and return type. However, it doesn't describe the expected DataFrame columns or the meaning of '分红融资' beyond a generic term, and lacks usage context compared to siblings.

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 one parameter 'symbol' with no description, but the description documents it as '股票代码' (stock code) with type str, and gives an example URL. This fills the gap partially, but lacks format details or exchange prefix guidance.

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 states '同花顺-分红情况' and includes a URL to a bonus page, plus a return type of DataFrame, indicating it retrieves dividend/financing data for a given stock from Tonghuashun. It doesn't explicitly contrast with sibling tools like stock_fhps_detail_em, but the name and source are clear.

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 when-to-use guidance is provided. There are multiple dividend-related sibling tools (stock_fhps_em, stock_history_dividend, etc.) but the description offers no criteria for selecting this specific tool, nor exclusions.

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