stock_sector_detail

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, so the description does not need to cover safety. It adds useful context about sector choices and the excluded sector, but does not describe pagination, rate limits, or the full return structure.

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 with a title, source URL, parameter documentation, and return type. No unnecessary words; it is front-loaded with the purpose. The docstring format is efficient.

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?

Without an output schema, the description should explain what '板块详情' concretely contains (e.g., constituent stock codes/names/prices). It only provides a broad phrase and a URL, leaving the agent to infer the DataFrame columns. This is a notable gap for a data-returning tool.

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 has 0% description coverage for the only parameter, but the description compensates by explaining that sector is the label from stock_sector_spot, listing the valid choices, and noting an excluded value. However, the schema default 'gn_gfgn' is not among the listed choices, creating potential confusion.

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 returns details for a specified sector, and the title/name ('成份详情', component details) imply constituent-level data. It distinguishes itself from stock_sector_spot (which lists sectors) but does not explicitly name the difference or state the exact output content.

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?

It explicitly directs the agent to obtain the sector label from stock_sector_spot, lists the valid choices for sector, and notes that '启明星行业' has no details. This gives clear when-to-use guidance, though it doesn't compare with other detail tools.

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