Skip to main content
Glama

Colour Memory

by app.railway.up.colour-memory-api-production
OverviewDiscussionsAdmin

Mix Two Colours (Pigment Simulation)

colour_mix
Read-only

Simulate perceptually modelled subtractive mixing of two colours in CIE Lab space (not RGB screen blending). Returns the resulting mixed hex value and its nearest archive match with cultural context. Uses CIE Lab subtractive model for perceptual accuracy. Example: mixing Prussian Blue and Yellow Ochre gives a muted green — the tool identifies which archive colour that green most closely matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hex_aYesFirst colour hex e.g. '#003366'
hex_bYesSecond colour hex e.g. '#C8A600'
ratioNoMix ratio 0.0-1.0 where 0.5 is equal parts (default 0.5)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "description": "Structured JSON response. Shape varies by tool; most return an 'ok' boolean plus a 'result' or 'results' field with the tool's data payload.",
+  "type": "object"
+}
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "error": {
-      "type": "string"
-    },
-    "ok": {
-      "type": "boolean"
-    },
-    "result": {
-      "type": [
-        "object",
-        "array",
-        "string",
-        "null"
-      ]
-    }
-  },
-  "type": "object"
-}New value: +null
  3. Added

TDQS

A4.7/5.0
Behavior5/5

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

The annotation readOnlyHint=true is consistent with the description, which adds rich behavioural context: the CIE Lab subtractive model, perceptual accuracy, and the nature of the output (nearest archive match with cultural context). This goes well beyond what the annotation alone conveys.

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?

Four sentences, each earning its place: the core function, the output, the model reinforcement, and a concrete example. It is front-loaded with the most important information and has no fluff.

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

Completeness5/5

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

The description covers purpose, method, output, and a worked example. Given the existence of an output schema and annotations, it is complete without needing to detail return structures or safety profile.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds semantic value through the example (Prussian Blue + Yellow Ochre gives a muted green), illustrating the intended meaning of the hex inputs as pigment colours. This helps the agent understand the parameters beyond their raw format.

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 states exactly what the tool does: simulate subtractive mixing of two colours in CIE Lab space, distinct from RGB screen blending, and returns the mixed hex plus nearest archive match. This is a specific verb+resource+method and distinguishes it from other colour tools.

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

Usage Guidelines4/5

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

It explicitly notes 'not RGB screen blending', which is a clear when-not situation. However, it does not name alternative tools for additive mixing or colour comparison, leaving the guidance slightly implicit. The example provides a concrete use context but no explicit alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Colour Memory toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources