regional_check

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the safety profile is clear. The description adds that it searches regional business info but does not disclose additional behavioral traits beyond what annotations provide. This is adequate but not enhanced.

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 a single, well-structured sentence that effectively communicates the tool's purpose. It is front-loaded with the main action and uses no extraneous 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 the tool's simplicity (one parameter, no output schema, annotations present), the description provides all necessary context for an AI agent to understand what the tool does and how to use it. No additional details are needed.

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 schema has one parameter 'query' with 100% coverage. The description adds meaning by providing example queries in Japanese, clarifying the expected format and content beyond the schema's bare description.

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 specifies it searches for Japanese regional business information including city characteristics, subsidies, ordinances, and customs. The name 'regional_check' clearly indicates a check/query function, and it distinguishes from sibling tools like 'regional_list' (which likely lists regions) and 'regulation_check' (more specific to regulations).

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 example queries like '大阪の飲食店条例' and '東京のスタートアップ助成金', giving clear context on when to use the tool. However, it does not explicitly state when not to use it or mention alternatives among the many sibling tools, leaving some ambiguity.

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