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ledfx_create_scene_from_description

Generates a dynamic LED scene from a natural language description, allowing you to match lighting to any mood or event.

Instructions

Create a scene from a natural language description (e.g., 'calm blue ocean waves' or 'energetic party rainbow')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
descriptionYesNatural language description of the desired scene
virtual_idsNoOptional list of virtual IDs to apply effects to. If not provided, uses all active virtuals.
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. The description only states what the tool does, not any behavioral traits such as side effects (e.g., overwriting scenes), required permissions, or how ambiguous descriptions are handled. This leaves significant uncertainty for the agent.

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?

The description is a single, clear sentence with no unnecessary words. Each part earns its place: the verb 'Create', the object 'scene', and the examples. No verbosity, perfectly concise.

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 has no output schema and moderate complexity (2 parameters, one optional), the description should disclose return behavior or prerequisites. It does not mention what happens after creation (e.g., auto-activation) or any dependencies like existing virtuals. This leaves the agent underinformed for a creation tool.

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

Parameters3/5

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

The input schema covers both parameters with 100% description coverage, so the schema already explains them. The description adds examples for the 'description' parameter but does not provide additional semantic meaning beyond what the schema offers. It meets the baseline but does not excel.

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 purpose: creating a scene from a natural language description. It provides two concrete examples ('calm blue ocean waves' and 'energetic party rainbow'), which make the intent immediately obvious. It also distinguishes itself from siblings like ledfx_create_scene, which likely requires structured input.

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 implies usage for quick, intuitive scene creation from natural language. However, it does not explicitly state when to use this tool versus ledfx_create_scene or alternatives like ledfx_apply_preset. No guidance on when not to use it or prerequisites is provided.

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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