Colour Memory

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

Product Line Colour Namer

ecommerce_namer

Read-only

Generate archive-grounded colour names for up to 40 product SKUs. Input: list of hex values, product category, brand name, naming style. Output: for each hex -- archive name, source citation, one-line product description, dE2000 match distance, match quality, and confidence score. Every name is archive-sourced, not invented. Each carries a primary source citation that can be defended to buyers, press, and brand teams. Use for paint ranges, candle collections, fashion lines, homeware, cosmetics. Style options: geographical, poetic, material, literary, mixed.

Input Schema

TableJSON Schema

Name	Required	Description
`hexes`	Yes	List of hex values e.g. ['#D4A829', '#1A5C6E']
`style`	No	geographical \| poetic \| material \| literary \| mixed (default)
`max_dE`	No	Max dE2000 distance to accept (default 25)
`brand_name`	No	Brand name for context
`product_category`	No	e.g. 'paint', 'candle', 'fashion', 'homeware'

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedJun 20, 2026

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"
+}

Changed1 schema field changedJun 17, 2026

changedOutput schema / (root)

Previous value: -{
-  "properties": {
-    "error": {
-      "type": "string"
-    },
-    "ok": {
-      "type": "boolean"
-    },
-    "result": {
-      "type": [
-        "object",
-        "array",
-        "string",
-        "null"
-      ]
-    }
-  },
-  "type": "object"
-}New value: +null

AddedJun 2, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations provide readOnlyHint=true, so safety is already declared. The description adds meaningful behavioral context: every name is 'archive-sourced, not invented' and carries a defensible citation. It also states the 40-SKU limit. These go beyond the annotation without contradicting it.

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 compact and front-loaded with the core action. It covers input, output, and use cases in a few sentences. The redundancy between 'Every name is archive-sourced, not invented' and the following citation sentence is minor but slightly bloats the text.

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?

For a tool with 5 parameters, an output schema, and read-only annotations, the description is complete: it states the input types, output format, use cases, and quality guarantees. It does not explain the behaviour of max_dE, but the schema describes it, so the gap is acceptable.

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?

Schema coverage is 100% and parameter descriptions are self-sufficient. The description repeats some parameter names (hexes, style, brand, category) and mentions style options already in the schema, but adds no new meaning beyond the schema. Baseline 3 applies because the schema does the heavy lifting.

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 opens with a specific verb+resource+constraint: 'Generate archive-grounded colour names for up to 40 product SKUs.' It clearly distinguishes from siblings like colour_namer by emphasizing 'archive-grounded' and the ecommerce context, and it enumerates the exact output fields.

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?

The description explicitly names target use cases ('Use for paint ranges, candle collections, fashion lines, homeware, cosmetics'), giving clear context. However, it does not state when to avoid this tool or name alternatives such as colour_namer, so it lacks the when-not/exclusion guidance for a 5.

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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