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

No annotations are provided, so the description bears the full burden and discloses almost nothing: it does not confirm read-only behavior, describe the response shape (buckets, scores, counts), or note any scope limits such as geography or data source. The word 'distribution' weakly implies an aggregate read, which is the only behavioral hint available.

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?

At six words it is maximally compact and front-loaded with the resource, with no filler. The brevity is under-specification rather than efficient concision, so it earns only a middling score.

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 one-parameter read tool this could be simple, but with no annotations, no output schema, and an unexplained min_score, an agent has nothing to reason from beyond the topic. It is not sufficient to invoke the tool confidently.

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 single optional parameter min_score is undocumented in both schema (0% coverage) and description, and its string type is unusual for something named like a numeric threshold. An agent cannot tell whether it accepts a number as text, a bucket label, or a comparison expression, so the description does not compensate for the coverage gap at all.

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?

The fragment 'ジオコーディング品質の分布' (geocoding quality distribution) narrows an ambiguous name (jp_quality) to a specific resource and implies a statistical/aggregate output, which is real information the name alone does not carry. However, it is a bare noun phrase with no verb, so it never states what the tool actually does — computes, lists, or summarizes — leaving the operation to inference.

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, no stated alternative among the many jp_* data siblings, and no indication of the scenario this distribution serves. The only implicit signal is that it is a quality/statistics lookup rather than a per-record query.

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