stock_board_industry_summary_ths

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is fully covered. The description adds value by specifying the source URL and the pandas.DataFrame return type, clarifying that the full industry overview list is returned. No contradiction with 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 compact at four lines and front-loads the source and resource. The first line redundantly repeats the title annotation, which costs a small amount of efficiency, but the URL and return-type lines earn their place. Overall well-sized with no filler beyond the title duplication.

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 zero-parameter, read-only summary tool with rich annotations, the description provides adequate context: the data source (THS data center), the exact URL, and the return type. The main gap is not enumerating the columns or contents of the overview table, but '一览表' (overview list) plus the sibling context makes the output scope reasonably clear.

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 there is nothing for the description to explain about inputs. Baseline of 4 applies, and the description appropriately focuses on the output instead of inventing parameter details. No parameter ambiguities exist.

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 identifies the resource as the THS industry overview table (同花顺行业一览表) from the THS data center, with an explicit :return: and :rtype: indicating a pandas DataFrame result. While the verb is implied rather than stated, the Chinese title and URL clearly convey a fetch/list operation. It does not explicitly differentiate from sibling industry-board tools like stock_board_industry_spot_em or stock_board_industry_name_ths.

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. Given many siblings cover industry boards (stock_board_industry_spot_em, stock_board_industry_index_ths, stock_board_concept_summary_ths, etc.), the description offers no contextual hint, exclusions, or alternative recommendations. The usage context is only implicitly inferable from the name and title.

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