空き家率統計

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds value by detailing the output structure (total vacant, for-rent, for-sale, other) and the comparison to national average. No contradictions or missing behavioral disclosures.

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 description is extremely concise (two short sentences covering English and Japanese), front-loaded with the key action and result, and every part is useful. No wasted words.

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?

Given no output schema, the description adequately explains the return values (categories and comparison). It does not cover pagination or data format, but for a statistics tool with a single-purpose query, this is acceptable and complete enough.

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%, but the description goes beyond by explaining the effect of omitting 'area' (returns prefecture-level data) and the formats for 'prefecture'. This adds meaningful context not captured in the schema's minimal descriptions.

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 explicitly states the verb (get), resource (vacancy rate statistics), and scope (by municipality, compared to national average). It clearly distinguishes from sibling tools like 'analyze_commute_accessibility' and 'forecast_land_price_trend' by focusing on a specific metric.

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?

The description provides clear guidance: use with 'area' for a specific municipality or omit for the full prefecture. While it does not explicitly list alternatives or when-not-to-use, the context is sufficient for choosing this tool over others.

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