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 usefully discloses the returned content and flags that the last buy-in date is '估算' (estimated), which is real behavioral context. It does not state data currency, source, or freshness limits, so it only partially compensates for the missing annotations.

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?

A compact two-part structure: the returned fields first, then the triggering scenarios. The leading bracket tag ［台美股題材與高股息］ is category noise with marginal value, but overall the text is front-loaded and earns its place.

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 does the necessary work by listing what the tool returns (dates, location, book-closure, buy-in, agent, e-voting). For a read-only lookup with no annotations it is largely complete, missing only data-source/freshness caveats.

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 the schema already documents all five parameters (code, days, from, kind, buy_window). The description only loosely relates to buy_window via the '最後買進日' mention and adds no syntax or default detail beyond the schema, so 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) plus resource (台灣上市公司股東會) and enumerates the exact fields returned: date, location, book-closure date, estimated last buy-in date, shareholder agent, and e-voting. This distinguishes it cleanly from sibling stock tools like get_tw_dividend or get_tw_ex_dividend.

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 names triggering user questions (「股東會紀念品最後買進日」「台積電股東會哪天」), which gives strong when-to-use context. However, it names no alternative tool and no exclusion conditions, so it falls short of full when/when-not guidance.

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