stock_board_industry_spot_em

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and non-destructive, so the safety profile is fully covered. The description adds that it returns a pandas.DataFrame and includes a source URL, which is helpful context. However, it doesn't disclose potential rate limits, error behavior, or what specific fields appear in the DataFrame, leaving some behavioral ambiguity beyond the 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 and well-organized: a title line, a source URL, then a docstring-style param/return block. Every sentence adds value (source for verification, param meaning, return type), and there is no fluff or repetition of schema data.

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?

The tool is simple (1 optional param, no output schema), and the description covers its core purpose, input meaning, and return type. However, it stops at '实时行情' without listing typical columns (e.g., 最新价, 涨跌幅) that would fully inform an agent about the output. Since there is no output schema, the description ideally should enumerate these fields to be truly complete.

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 input schema provides no description for 'symbol', yet the description explicitly defines it as '板块名称 or 东财板块代码' (sector name or Eastmoney code) and specifies the type 'str'. It also indicates the return type. With 0% schema coverage, this fully compensates for the missing structured documentation.

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 '东方财富网-沪深板块-行业板块-实时行情' (Eastmoney Shanghai/Shenzhen industry sector real-time quotes), specifying the verb (get real-time quotes), resource (industry sectors on SSE/SZSE), and scope. It includes a source URL and distinguishes itself from siblings like stock_board_industry_hist_em (historical) and stock_board_industry_cons_em (constituents) by emphasizing '实时行情'.

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 conveys clear usage context: to get real-time quotes for an industry sector, provide either a board name or Eastmoney code as the 'symbol' parameter. The default value '小金属' gives an example. It does not explicitly mention alternatives or exclusions, but the '实时行情' wording makes it obvious when this tool is appropriate relative to historical or constituent-focused siblings.

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