Set the Rhino viewport's background color by specifying RGB values from 0 to 255, enabling custom visual work environments.
Set the viewport background color via a Python script.
Args:
r, g, b: RGB color components (0-255).
| Name | Required | Description | Default |
|---|---|---|---|
| b | No | ||
| g | No | ||
| r | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action and the 'via a Python script' mechanism, but does not clarify whether the change affects the active viewport or all viewports, whether it persists, or whether it impacts rendering output. For a mutation-style tool, this lacks important behavioral context.
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?
The description is exceptionally concise: one front-loaded purpose sentence followed by a minimal parameter list. Every word earns its place and there is no redundant or filler content.
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 3-parameter setter, the description is mostly adequate: it conveys purpose and parameter semantics. The gaps are the missing viewport targeting scope (active vs all), persistence, and whether the change affects rendering. One or two clarifying sentences would make it fully complete.
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?
With 0% schema description coverage, the description fully compensates by documenting all three parameters (r, g, b), explaining they are RGB color components, and specifying the valid 0-255 range. This is precisely the information an agent needs to construct valid input values.
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 states a specific verb ('Set') and resource ('viewport background color'), making the tool's purpose immediately clear. This distinguishes it from related sibling tools like rhino_environment_set and rhino_display_mode_set, which target different aspects of the viewport/rendering environment.
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?
Usage is implied by the description: an agent would know to use this tool when it wants to change the viewport background color. However, there is no explicit when-to-use guidance, no mention of prerequisites (such as an active viewport), and no comparison with alternative or related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.