industry_classify

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

没有任何 annotations，因此描述需要承担行为透明度的全部责任。它明确表明这是读取/获取操作，并列出两个数据源，基本行为可预期；但未说明列表是扁平还是层级结构，也未涉及更新频率或缓存行为。考虑到输出 schema 已存在，这些缺口不算致命，但仍是简单的最小披露。

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?

描述只有一句话，动词和宾语前置，没有任何冗余信息。对于这样一个单参数、简单列表获取工具，长度和结构都恰到好处。

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?

作为带输出 schema 的简单分类列表工具，描述接近够用，但没有说明两个可选来源之间的适用差异，也没有在众多行业类兄弟工具中定位自身。代理在需要判断是否应该选择该工具而非行业树、行业成分股或行业行情工具时，缺乏足够的上下文。

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?

参数 schema 覆盖率为 100%，唯一参数“分类标准”已有默认值和可选范围（同花顺/巨潮）的说明。描述本身只是在重复数据源名称，没有增加超出 schema 的参数语义信息，因此按高覆盖率的基线评 3 分。

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?

描述使用明确动词“获取”和具体资源“同花顺/巨潮行业分类列表”，让工具功能清晰可辨。虽然没有显式说明与行业类兄弟工具（如 industry_sw_tree）的区别，但列出的数据源已经提供了部分区分度。

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?

描述没有说明何时使用该工具、何时不应使用，也没有提及替代工具或选择同花顺与巨潮标准的场景。面对大量行业相关兄弟工具，代理只能从工具名称和“分类”一词推断用途，缺少主动引导。

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