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Get structured weather

get_structured_weather

Retrieve structured weather data for Zurich or Savognin as a typed object, enabling output schema validation.

Instructions

Return a typed Weather object so the client can validate it against the output schema.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
locationNoZurich

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
humidityYesRelative humidity as a percentage
locationYesCity the reading is for
conditionsYesHuman readable sky conditions
temperatureYesTemperature in degrees Celsius
Behavior4/5

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It clearly describes a read-only operation that returns a typed Weather object, which is sufficient for a simple getter. It could mention error behavior or live-data assumptions, but the core behavior is not hidden.

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?

A single sentence with no wasted words: it states the return value and the client benefit, and the key idea is front-loaded. Nothing extraneous is present.

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

Completeness3/5

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

The output schema covers the return shape, and the parameter schema covers location, so the main missing piece is when to use this structured tool versus alternatives like weather_report. The absence of annotations also leaves behavioral caveats unstated, though the tool is simple enough that this is a moderate gap rather than a severe one.

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

Parameters2/5

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

Schema description coverage is 0%, yet the description contributes nothing about the location parameter or how to choose between Zurich and Savognin. The enum and default in the schema help, but the low-coverage rule expects the description to compensate, and it does not.

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

Purpose4/5

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

The description states a specific action ('Return') and resource ('a typed Weather object'), and its emphasis on typed/schema-validateable output makes the structured nature clear. It does not name a sibling such as weather_report, so the differentiation is implied rather than explicit.

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

Usage Guidelines3/5

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

The phrase 'so the client can validate it against the output schema' gives a clear context for the structured return value, but the description never says when to prefer this over weather_report or when not to use it. Usage guidance is implied by the name and typing, not stated.

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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