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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations: the data source (Tokyo Bureau of Social Welfare), station coverage, and the special in-station layer grouped by ticket gate and railway operator for major stations. This gives the agent a clear picture of edge-case behavior.

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?

Three sentences, each earning its place: the first states the core purpose and output fields; the second defines coverage and special behavior for major stations; the third specifies input formats with examples. No fluff, well front-loaded, and appropriately sized for the tool's complexity.

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), the description covers all essential aspects: what it retrieves, the geographic scope, data source, input varieties, and special grouping behavior for major stations. An output schema exists, so return-value details are already structured. The description is complete for safe and correct invocation.

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 covers the single parameter with 100% coverage, providing the baseline of 3. The description enhances this by explaining accepted formats (Japanese and romaji), providing examples, and clarifying that romaji is only for major stations. This adds practical guidance for correctly filling the parameter.

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 uses a specific verb ('look up') and clearly identifies the resource: wheelchair-accessible/multipurpose toilets inside train stations. It enumerates details (floor, gender, equipment, nearest exit) and distinguishes itself from sibling tools like get_public_toilet_by_city, which focuses on city-level public toilets.

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 context: it works for 526 Tokyo stations and major stations outside Tokyo with a different grouping behavior. It also specifies acceptable input formats (Japanese/romaji) and hints that romaji is only for major stations. However, it does not explicitly state when NOT to use it or name alternative tools, so it stops short of a full 5.

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