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RNVizion

rnv-color-mcp

Official

mix_colors

Blend up to 12 colors into one using perceptual Lab, RGB, HSV, paint, RYB, or CMYK models. Supports hex, CSS names, and palette references. Returns hex and RGB.

Instructions

Blend up to 12 colors into one. Each color may be a hex (#d2bc93), a CSS name (red), an RNV brand name (brand gold, near-black), or a saved-palette reference (Spring line, or 'Spring line:2' for its 2nd swatch). Optional integer weights bias the blend (defaults to equal). mode selects the model: rgb/hsv/lab are digital blends (lab is perceptual and the default); paint mixes pigments via Kubelka-Munk physics (colors darken like real paint); ryb is the artist's color wheel; cmy is subtractive like printer inks. Returns hex and rgb.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNolab
colorsYes
weightsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Describes return values (hex, rgb), optional weights, mode options with explanations (digital vs paint), though lacks disclosure on side effects or performance implications.

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?

Dense but informative single paragraph; could be structured with bullet points for readability, but all sentences add value.

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

Completeness4/5

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

Covers inputs, modes, and return types; minor gaps on weight-colors alignment and output schema structure, but largely complete given complexity and output schema existence.

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 coverage, description fully explains all parameters: colors format, weights, mode choices and defaults, adding significant meaning beyond the schema.

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?

Clearly states the tool blends colors, specifies input types and modes, and is distinct from sibling tools like color_difference or convert_color.

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

Usage Guidelines2/5

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

No guidance on when to use this tool vs siblings or alternatives; does not mention prerequisites or exclusion criteria.

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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