stock_industry_clf_hist_sw

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds the source URL and return type (pandas.DataFrame), which is useful context, but it does not disclose further behavioral traits such as data scope, date range, or potential errors.

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 efficient, containing a source URL, a return line, and a return type. The title line is somewhat redundant with the annotations but does not add significant waste.

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 parameter-less, read-only tool with good annotations, the description is mostly adequate. However, it lacks details about the actual content of the returned DataFrame (e.g., columns, date range, coverage), and there is no output schema to compensate for this gap.

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 tool has zero parameters, so the baseline score of 4 applies. No parameter explanation is needed.

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 '个股行业分类变动历史' (individual stock industry classification change history), which identifies a specific operation and resource. However, it does not explicitly differentiate from sibling tools like stock_industry_change_cninfo, though the 'sw' and 'hist' hints in the name provide some distinction.

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. The description merely states what it returns, with no mention of use cases, exclusions, or relationship to other stock industry tools.

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