町丁目レベル10年後人流・人口動態予測

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description is not required to repeat that safety profile. The description adds context by naming data sources ('国勢調査・人流統計') and output types ('10年後の人口・世帯・高齢化率'), but does not disclose any additional behavioral traits such as data freshness, model assumptions, or rate limits. This adds some value beyond annotations but remains limited.

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 two sentences with bilingual repetition (English and Japanese). It is reasonably concise but includes redundant information. The first sentence provides the core purpose; the second sentence repeats it in Japanese with slightly more detail. It could be more efficient by combining the two or removing the duplicate.

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?

Despite having an output schema, the description is insufficient for a forecasting tool with 5 parameters. It does not explain the prediction methodology, the required input combinations (e.g., is neighborhood required? what about lat/lng?), or any important limitations. The agent needs more context to select and invoke this tool correctly, especially given the complexity of demographic prediction.

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 60%, with city, prefecture, and neighborhood having descriptions, but latitude and longitude have no description. The tool description does not explain how the parameters relate to each other or provide guidance on which are necessary beyond the required city. It fails to compensate for the missing descriptions of latitude and longitude, so the agent receives no additional meaning for those parameters.

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 clearly states the tool predicts demographic, aging, and human flow trends at the neighborhood or city level, with specific reference to 10-year forecasts. It uses a specific verb ('predict' and '予測する') and resource ('demographic, aging and human flow trends', '人口・世帯・高齢化率'), and distinguishes it from siblings like forecast_land_price_trend which predict land prices.

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?

No explicit guidance is given on when to use this tool versus alternatives. The description does not mention any conditions, prerequisites, or exclusions. Given the many sibling tools for forecasting and simulation, this leaves the agent without direction on appropriate contexts.

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