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Answer Japan Seasonal Travel Question

japan_seasonal_answer
Read-onlyIdempotent

Answer broad Japan seasonal travel questions by routing to live datasets for cherry blossoms, autumn leaves, festivals, and more. Get ready-to-use recommendations based on your travel dates and location.

Instructions

Use this first when the user asks a broad Japan seasonal travel question, including cherry blossom forecasts, autumn leaves, flowers, festivals, fruit picking, or what is good during travel dates. This is the best entry point for natural traveler prompts because it routes to the right live dataset and returns a ready-to-use recommendation. Do not use this for hotels, flights, trains, visas, restaurants, or generic itinerary planning unrelated to seasonal timing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionNoThe user's natural-language question, for example 'How is the sakura forecast?', 'Where should I see autumn leaves in late November?', or 'What seasonal things are good in Japan in June?'
start_dateNoOptional trip start date in YYYY-MM-DD format. Provide this when the user gives travel dates.
end_dateNoOptional trip end date in YYYY-MM-DD format. Provide this when the user gives travel dates.
locationNoOptional city, prefecture, or region such as Tokyo, Kyoto, Hokkaido, Kansai, Tohoku.
seasonNoOptional explicit season/topic. Use auto unless the user clearly asks for one topic. Use overview for broad questions about what seasonal activities are good in a month.
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so safety is covered. Description adds value by explaining it routes to the right live dataset and returns a ready-to-use recommendation. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two essential sentences plus a clear exclusion list. Front-loaded with purpose. No fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of seasonal travel questions and many sibling tools, the description covers purpose, usage, limitations, and expected output (ready-to-use recommendation). Complete for its context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and parameter descriptions are detailed (e.g., enum for season explained). Description adds contextual guidance for dates ('Provide this when the user gives travel dates') and location, which helps agents use parameters correctly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it handles broad Japan seasonal travel questions, listing specific topics like cherry blossoms and autumn leaves. It explicitly differentiates from siblings by stating what not to use it for (hotels, flights, etc.).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use this first' for broad seasonal questions and lists exclusions (hotels, flights, trains, visas, restaurants, generic itinerary). Provides clear when-to-use and when-not-to-use guidance.

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

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