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Colour Memory

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

Make Any Colour Memorable

colour_hooks
Read-only

Generate a hook sentence, three-sentence story, tweet, image prompt, and follow-up questions for any hex colour. Backed by the nearest archive colour's cultural provenance. Tunable by audience (general public, designers, historians, children) and tone (dinner party, academic, social media, brand copy). Use to make archive colours shareable, to generate content, or to power a public-facing colour chat experience.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hexYesHex colour e.g. '#154F20'
toneNoDesired tone e.g. 'dinner party', 'academic', 'social media', 'brand copy'dinner party
audienceNoTarget audience e.g. 'general public', 'interior designers', 'children'general public

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

A4.3/5.0
Behavior4/5

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

Annotations only state readOnlyHint: true. The description adds valuable behavioral context by disclosing that outputs are 'backed by the nearest archive colour's cultural provenance' and that the tool is tunable by audience and tone. This goes beyond the annotation's simple safety hint and explains what the tool actually does with inputs.

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 two sentences that front-load the primary action and outputs, followed by concise use cases. No wasted words; every sentence earns its place. This is an example of efficient, well-structured tool documentation.

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?

Given the tool's generative nature, the description lists all output types (hook, story, tweet, image prompt, follow-up questions) and presents relevant usage scenarios. An output schema exists to detail return values, so the description does not need to cover those. The description is complete for an agent to decide when and how to use the 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?

Schema coverage is 100% with clear descriptions for hex, tone, and audience. The description's mention of tunable audience/tone examples ('general public, designers, historians, children') largely mirrors the schema's own examples. It adds minimal extra meaning, such as 'any hex colour', which does not significantly exceed what the schema already conveys.

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 ('Generate') and lists concrete outputs (hook sentence, three-sentence story, tweet, image prompt, follow-up questions) for a hex colour. It clearly distinguishes this tool from siblings like colour_story or colour_namer by focusing on multi-format content generation grounded in archive provenance.

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 provides explicit use cases ('Use to make archive colours shareable, to generate content, or to power a public-facing colour chat experience'), giving clear context for when to invoke it. It does not explicitly mention when not to use it or name alternatives, so it falls short of a 5 but is well above vauge guidance.

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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