Japan Weather Forecast

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

Annotations already declare readOnlyHint=true and idempotentHint=true, indicating safe, idempotent operation. The description adds context: it returns forecast text, temperatures, and rain probabilities, and specifies the data source (Japan Meteorological Agency). It could mention potential error conditions or rate limits, but it is sufficiently transparent given the annotations.

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 serving a purpose: usage context, what it returns, and what not to use it for. No redundant or filler content. Front-loaded with the most important usage 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?

For a simple tool with one parameter and no output schema, the description fully explains the return data (forecast text, temps, rain probabilities) and time range (next 3 days). It also provides usage context and limitations. No gaps given the tool's complexity.

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 provides 100% coverage with a detailed description of the 'city' parameter including the full list of supported cities and partial case-insensitive matching. The description does not add significant new information beyond what is in the schema, but it does reinforce that it is for one supported city. Baseline score of 3 is appropriate.

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 it returns short-range weather forecast data (next 3 days) including JMA forecast text, temperatures, and rain probabilities for a supported city. It also distinguishes itself from seasonal bloom tools by specifying that it is not for sakura or 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 tells when to use (when short-range weather could affect recommendations) and when not to use (for seasonal bloom timing months in advance), and names the alternative tools (sakura or koyo forecast tools). This provides clear guidance for selection.

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