stock_board_industry_hist_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the data source URL and return type (pandas.DataFrame) but does not disclose other behavioral traits such as rate limits, date format constraints, or empty-result behavior. Since annotations cover the main safety aspects, this is acceptable but not exceptional.

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 a compact docstring with a clear title line, a source URL, and parameter documentation. Every line carries meaningful information with no redundancy or filler. It is well-structured and front-loaded.

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 has five parameters and no output schema, so the description should cover return semantics and usage context. It states the return is '历史行情' as a DataFrame, which is sufficient for basic use, but it lacks details about the columns, the list of valid sector symbols, and how it compares to the many sibling board-related tools. This leaves some ambiguity for an agent deciding among similar 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?

With schema description coverage at 0%, the description carries the burden of explaining parameters. It provides Sphinx-style docs for all five parameters, including explicit choices for period ('日k', '周k', '月k') and adjust ('', 'qfq', 'hfq'). However, it does not specify the date format for start_date/end_date beyond the defaults, and symbol values are described only as '板块名称'. This is helpful but has minor gaps.

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 opens with '东方财富网-沪深板块-行业板块-历史行情', clearly stating it provides historical quotes for Shanghai/Shenzhen industry sectors from Eastmoney. This specific verb+resource combination distinguishes it from sibling tools like stock_board_industry_spot_em (spot) and stock_board_industry_cons_em (constituents).

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 usage through the word '历史行情' (historical quotes) and the source URL, but it provides no explicit guidance on when to use this tool versus alternatives such as stock_board_industry_spot_em or stock_board_industry_hist_min_em. There are no exclusion criteria or prerequisites mentioned, so it only partially addresses usage context.

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