Japan Weather Forecast

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

Annotations already declare readOnlyHint and idempotentHint true, so the description's added value is limited to return content details and city scope. No contradictions, but does not add significant behavioral context beyond what annotations provide.

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?

Extremely concise: two sentences, zero waste. The first sentence clearly states the primary use case, the second provides exclusions and alternatives. Front-loaded with key guidance.

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 an output schema exists (not shown but indicated) and the tool has only one parameter, the description covers all necessary aspects: purpose, usage context, and constraints. No gaps for an AI agent to invoke correctly.

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 coverage is 100%; the description does not add meaning beyond what the schema's property description already provides. The tool has only one parameter, and the description clarifies the city-specific scope, but this is implicit in the schema.

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?

Description uses a specific verb ('returns') and specifies the resource ('next 3 days of Japan Meteorological Agency forecast text, temperatures, and 6-hour rain probabilities for one supported city'). It also distinguishes from sibling tools (sakura/koyo forecasts).

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?

Explicitly states when to use ('short-range weather could change recommendation') and when not to ('Do not use for seasonal bloom timing months in advance'), with clear alternatives (sakura or koyo forecast tools).

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