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

With no annotations provided, the description carries the full behavioral burden. It discloses what fields come back (配息、除息日、發放日) but says nothing about data freshness, which years/periods are covered, or the fallback behavior (that an empty code returns a summary table, which lives only in the schema). Read-only nature is only implied.

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 single, front-loaded sentence with a bracketed category tag followed by purpose and output fields. No wasted text, though the bracketed label adds mild redundancy without functional value.

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?

For a simple one-parameter read tool with no output schema and no annotations, the description covers purpose and examples but omits the temporal scope of the dividend data and the summary-table fallback. Adequate but with clear gaps an agent would want before invoking.

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%: the single 'code' parameter is already documented as "ETF 代號；不填回傳總表". The description adds useful example codes but does not explain the parameter's behavior or the no-code fallback, so a 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?

States a specific verb (查詢) with a clear resource (台股高股息 ETF 每期配息、除息日、發放日), and even enumerates concrete examples (0056、00878、00919 等). It is easy to tell the tool retrieves actual per-period dividend records, though it never explicitly contrasts itself with the sibling stocks__estimate_etf_dividend_2027, so it stops short of full sibling differentiation.

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?

There is no when-to-use guidance and no routing to alternatives such as stocks__estimate_etf_dividend_2027 (forward-looking estimate) or stocks__get_stock. The agent must infer usage purely from the description's topic, which is thin guidance for a data-lookup tool.

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