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

No annotations are provided, so the description carries the full load, and it does disclose the data vintage (FY2025), the source, and the shape of the result for each call mode — including that the job-only case returns a ranked list. It omits error behaviour, refresh cadence, and any rate/permission notes, which is why it is not a 5.

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?

Extremely compact, front-loaded with the dataset and source, then the coverage, then the three call modes. Every clause carries information an agent would otherwise have to infer; nothing is redundant.

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 two-optional-parameter lookup with no output schema and no annotations, the description covers origin, year, granularity, and result shape for every call mode. The remaining gap is the absence of valid-value guidance for the free-text job/prefecture strings, which matters because neither parameter has an enum.

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 coverage is 100% so the baseline is 3; the description exceeds it by specifying that omitting both parameters yields a listing and by defining the exact semantics of each one-parameter versus two-parameter call. It still does not enumerate the valid job/prefecture strings, and there are no enums.

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?

Names the exact resource (有効求人倍率), the statistical source (厚生労働省「一般職業紹介状況」), the fiscal year, and the granularity (23 jobs × 47 prefectures). The verb is only implied (a lookup), which keeps it from a 5, but an agent cannot mistake what data this returns.

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 maps each parameter combination to an outcome: prefecture only → that prefecture's 23 jobs, job only → 47 prefectures ranked descending, both → a single figure plus national rank. That is strong when-to-use-which guidance, though it never names or defers to the siblings (get_industry, list_industries) or states when not to use it.

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