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

No annotations are provided, so the description carries the full burden. It discloses that the tool is read-only and that shareholder count data follows periodic report disclosure (quarterly). This adds meaningful behavioral context beyond the schema, though it does not cover error handling or authentication.

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 concise and well-structured, starting with the purpose, then trigger phrases, an exclusion with an alternative, and a note on read-only and data frequency. Each sentence adds value without redundancy.

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?

Given the tool's simplicity (one parameter) and the presence of an output schema, the description covers all essential context: purpose, usage triggers, exclusions, and data freshness. Nothing critical is missing for an agent to invoke it correctly.

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?

Only one parameter (code) exists, and the schema already provides its description and example ('sh600667'). Since schema description coverage is 100%, the tool description adds no additional parameter meaning, so the baseline 3 is appropriate.

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 the tool's scope: shareholder research covering top ten shareholders, shareholder count (chip concentration), and institutional holdings. It also lists specific user query triggers ('谁在持有/股东变化/筹码集中/机构持仓'), making the purpose unambiguous and differentiating it from siblings like ashare_lhb.

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?

Explicitly specifies when to use this tool (when users ask about holders, shareholder changes, chip concentration, institutional holdings) and when not to, directing users to ashare_lhb for overall institutional buying. This is clear, actionable guidance with an alternative.

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