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set_weather

Apply weather conditions to a CARLA simulation world, with presets like clear, rain, fog, and night, and control intensity from 0 to 1.

Instructions

Apply a weather condition to the world without spawning agents.

Args: condition (str): One of clear, rain, fog, night, rain_night. intensity (float): Severity from 0.0 (minimal) to 1.0 (maximum).

Returns: dict: The execution result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conditionYes
intensityYes
Behavior3/5

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

Even without annotations, the description discloses that it does not spawn agents and returns a dict execution result. However, it does not cover potential side effects, authorization needs, or persistence of the weather condition.

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

Conciseness4/5

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

The description is well-structured with a clear purpose sentence followed by Args and Returns sections. It is concise but includes necessary details; a slightly shorter format could improve conciseness.

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?

Given the tool's simplicity (2 parameters, no output schema), the description covers purpose and parameters adequately. However, it does not explain error handling, out-of-range behavior, or the exact structure of the execution result dict.

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

Parameters5/5

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

With 0% schema description coverage, the description fully compensates by enumerating valid condition values ('clear', 'rain', etc.) and specifying intensity as a float from 0.0 to 1.0, enabling correct parameter selection.

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 the tool's action ('Apply a weather condition') and the resource ('to the world') with a distinguishing scope ('without spawning agents'), differentiating it from sibling tools that likely involve agents.

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 description lists valid conditions and intensity range, implicitly guiding usage, but lacks explicit when-to-use or when-not-to-use guidance compared to sibling tools. No alternatives mentioned.

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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