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

No annotations are provided, so the description carries the full burden and does so well: it discloses null handling for counties like 連江縣 (null means missing, not 0, with explanation in notes), the deliberate omission of the upstream 'compared with last month' field and why, and that dataPeriod is the requested year-month rather than the site's actual period. Auth, rate limits, and pagination are not addressed, but they are likely not relevant for a zero-param read.

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 purpose is front-loaded, then each semicolon-separated clause adds a distinct behavioral fact (null semantics, excluded comparison field, dataPeriod). It is dense but nearly every clause earns its place. A slightly tighter phrasing could improve readability, but there is no filler.

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 annotations, no output schema, and zero parameters, the description must carry the behavioral load, and it covers the key return semantics: the notes field, null vs 0, and dataPeriod. It does not enumerate the full output shape (e.g., the county-count mapping field), leaving a small gap.

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 tool takes zero parameters, so the baseline is 4. The description adds meaning about the one implicit input, the statistical year-month being determined by the website and echoed as dataPeriod, which is useful context even without a schema field.

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 a precise resource (行人穿越道退縮完成數 per county, current count per website legend). This is far beyond a tautology and tells an agent exactly what data it retrieves. It does not explicitly contrast with a named sibling, which keeps it just short of 5.

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?

Clearly scopes the tool: current counts only, no unit, no totals, no good/bad judgment, and deliberately no month-over-month comparison field. This tells the agent when the output is and isn't the right source. There is no explicit routing to an alternative tool for totals or comparisons, so it stops at clear context rather than 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.