stock_zyjs_ths

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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds the source URL and return type but does not disclose any behavioral nuances such as rate limits, network dependency, or error handling. With annotations covering safety, this is adequate but minimal.

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 concise and follows a structured docstring format with title, URL, param, and return fields. It is front-loaded with the title and source. The first line is redundant with the annotations title, which slightly detracts, but overall it is efficient and scannable.

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 tool with no output schema, so the description must clarify the return value. It vaguely states '主营介绍' (main business introduction) and returns a DataFrame, but does not describe columns, data granularity, or example content. The hardcoded URL for stock 000066 could mislead an agent into thinking the tool only works for that stock. No usage guidance is provided despite many similar sibling tools.

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 only lists 'symbol' as a string with a default. The description adds that symbol is a 股票代码 (stock code) and provides an example URL using '000066', giving meaningful context beyond the bare schema. However, it does not specify whether the code needs zero-padding, exchange prefix, or other formatting details.

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 the tool provides '同花顺-主营介绍' (THS main business introduction), with a URL indicating the source and a return type of pandas.DataFrame. It clearly identifies the resource and operation, though it could be more explicit about the specific fields or content of the returned data. It is distinguishable from siblings by the 'ths' suffix and Chinese name.

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 other stock-related tools such as stock_zygc_em or stock_financial_abstract. The description lacks any context about data source preference, use cases, or alternatives.

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