stock_board_concept_name_ths

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

The annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds the source URL and return type (pandas.DataFrame) but does not disclose additional behavioral traits such as rate limits, data freshness, or potential network dependencies. For a simple read-only tool with annotations, this is adequate but not enhanced.

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 extremely concise, consisting of a title, source URL, return value description, and return type. Every line serves a purpose, and there is no redundant or filler content. It front-loads the essential information.

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?

With no output schema and no parameters, the description carries the full burden of explaining what the tool returns. It clearly states that it returns all concept sector names and links in a pandas.DataFrame, which is sufficient for a simple list tool. It could be slightly more explicit about the exact column names, but the current description is adequate.

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 no parameters, so the input schema is trivially fully covered. The description is not required to explain parameters, and it doesn't attempt to. The baseline for zero-parameter tools is 4, and the description appropriately focuses on what is returned.

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 returns '所有概念板块的名称和链接' (names and links of all concept sectors) from 同花顺 (THS), which is a clear verb+resource. The source (THS) and scope (concept sectors) distinguish it from sibling tools like stock_board_concept_name_em and stock_board_industry_name_ths, though it does not explicitly name these alternatives.

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?

The description implies the tool is for obtaining the full list of THS concept sector names and links, providing clear context. However, it offers no explicit guidance on when to use this over other sibling tools (e.g., stock_board_concept_info_ths for details or stock_board_industry_name_ths for industry sectors), nor does it mention exclusions.

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