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

No annotations are supplied, so the description carries the full burden. It does not disclose the time period covered, whether values are raw counts or normalized rates, the data vintage, or any caveats about the source (総務省統計局 base data). For a statistics tool with zero annotation coverage this is a substantial gap.

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 compact sentence with no filler, and the data source is front-loaded. It is efficient, though brevity here comes at the cost of the missing details noted elsewhere.

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, no annotations, and an undocumented parameter, the description would need to explain return shape, units, and time coverage. It supplies none of these, leaving the agent unable to call 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?

Schema description coverage is 0% for the single required parameter 'prefecture', and the description adds nothing about its expected format — Japanese prefecture name, romaji, or code. With one undocumented parameter the description should compensate but does not.

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 description names a specific resource (刑法犯認知件数, penal-code offense counts) and a scope (都道府県別, by prefecture), so the general subject is identifiable. However, the framing as a 'シグナル' (signal) is vague about what is actually returned, and nothing distinguishes it from siblings such as jp_quality or jp_density that also emit prefecture-level indicators.

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 statement of when to use this tool, when not to, or which sibling to prefer for related prefecture statistics. The agent must infer usage purely from the topic word 'crime'.

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