industry_quotes

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

With no annotations supplied, the description carries the behavioral disclosure burden. It does disclose a useful non-obvious behavior: prioritizing local cache. However, it stops short of explaining what happens when the cache is missing or stale, whether it falls back to live fetching, or any other side effects.

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 single compact sentence with no filler. It front-loads the core purpose and includes the cache behavior at the end. Slightly more structure or explicit separation of data categories would help, but the length is appropriate.

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?

Although an output schema exists, the description lacks the routing context needed to select this tool correctly among many industry/sector siblings. It does not mention data freshness, fallback behavior, or when to prefer this cached quote tool over industry_capital_flow, industry_sw_daily, or sector_valuation. This incompleteness is material given the large sibling set.

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 schema already documents period and industry, covering 67% of the parameters. The description adds little beyond confirming the industry context. The limit parameter has no description in the schema and is not explained in the description, so agents receive no semantic help for it.

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 uses a specific verb ('获取') and a clear resource ('行业历史行情') plus concrete data types (OHLCV, 估值水平, 资金流向). It is clear about what the tool provides, but it does not distinguish it from closely related siblings like industry_capital_flow, industry_sw_daily, or sector_valuation.

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?

No explicit guidance is given for when to use this tool versus alternatives. The only contextual hint is '优先本地缓存', which implies a preference for cached data, but it never names sibling tools or states conditions for choosing this over them. Given the large number of overlapping industry/sector tools, this is a significant gap.

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