stock_sector_spot

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, covering the safety profile. The description adds the data source (Sina) and return type (pandas.DataFrame), which is useful but does not disclose any rate limits, pagination, or data freshness behavior. This aligns with the calibration example where annotations lower the burden but the description still lacks rich behavioral context.

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 functional, consisting of a title, source URL, and docstring-style parameter/return annotations. There is no wasted text, and the structure is clear. It is slightly sparse, but every line serves a purpose.

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, the description should explain the return data more thoroughly. It only states '指定 indicator 的数据' (data for the specified indicator) and the rtype, leaving column names or data granularity unspecified. The tool is simple, and the parameter choices are covered, but the return structure is a notable gap.

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?

Schema coverage is 0%, but the description compensates by listing the allowed values for the 'indicator' parameter: {'新浪行业', '启明星行业', '概念', '地域', '行业'}. This adds significant meaning beyond the schema's basic type/string and default definition, though it does not explain what each choice returns in detail.

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 it retrieves sector quotes from Sina Finance with the Chinese phrase '新浪行业-板块行情' and provides the source URL. It is specific about the resource (sector quotes) but does not explicitly differentiate from sibling tools like stock_sector_detail or stock_sector_fund_flow_rank, hence not a 5.

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 provides no guidance on when to use this tool versus alternatives. It lists parameter choices but does not mention any exclusions, prerequisites, or contextual scenarios. The only implicit usage is from the tool name and the description's mention of different indicator categories, which is insufficient.

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