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

No annotations exist, so the description carries the behavioral burden. It helpfully flags that the last-buy date is 估算 (estimated), which is real behavioral context, but says nothing about return format, pagination, or data source currency for a tool returning multiple fields.

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?

Two sentences, front-loaded with the capability then the usage trigger, with no filler. The field enumeration is dense but each item earns its place by telling the agent what comes back.

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 and no annotations, the description compensates by listing the returned fields and usage triggers, which is enough to call the tool correctly. It could still say more about the estimated-date caveat or data freshness, but overall it is complete enough.

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 description coverage is 100%, so all five parameters (code, days, from, kind, buy_window) are already documented in the schema. The description adds no parameter-level syntax or defaults beyond that, so the baseline 3 applies.

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?

States a specific verb (查詢/query) and resource (台灣上市公司股東會) and enumerates the returned fields (日期、地點、停止過戶日、最後買進日、股務代理、電子投票). No sibling tool covers shareholder meetings, so the agent can distinguish it immediately.

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?

Gives concrete trigger examples (「股東會紀念品最後買進日」「台積電股東會哪天」) that map user intent to this tool. It stops short of naming alternatives or when-not-to-use conditions, but the context is clear.

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