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Colour Memory

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

Is This Palette Working?

palette_verdict
Read-only

Evaluate a palette of 2-8 hex values for a use case, market, and medium. Returns a verdict (strong / strong_with_adjustment / weak / avoid), a score 0-100, the role of each colour, the single biggest weakness, and a concrete suggestion for what to add to fix it. Each colour is matched to the nearest archive entry for cultural grounding. Examples: 'premium cushion collection UK ecommerce', 'hotel lobby interior', 'SaaS brand identity global digital'. The result already carries the rendered palette and its PNG, PDF, ASE, JSON and CSS downloads, ready to show the customer. The archive anchors a colour was derived from are evidence, not the recommended colours. A final palette chosen from this evidence is registered with palette_finalize, called once with those exact colours, so the customer can see and download what was actually recommended.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "palette": "<palette>",
      "use_case": "<use_case>"
    },
    "name": "palette_verdict"
  }
}

Input Schema

NameRequiredDescriptionDefault
marketNoOptional: target market e.g. 'UK', 'Japan', 'global'
mediumNoApplication medium e.g. 'interior', 'digital', 'fashion', 'print'general
paletteYesList of 2-8 hex values e.g. ['#31559B', '#E8D898', '#4A2A50']
use_caseYesWhat the palette will be used for e.g. 'luxury cushion collection', 'brand identity'

Output 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. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "error": {
+      "type": "string"
+    },
+    "ok": {
+      "type": "boolean"
+    },
+    "result": {
+      "type": [
+        "object",
+        "array",
+        "string",
+        "null"
+      ]
+    }
+  },
+  "type": "object"
+}
  4. Added

TDQS

A4.1/5.0
Behavior4/5

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

Consistent with readOnlyHint=true — this is purely an evaluation. The description goes well beyond annotations by disclosing that the result carries a rendered palette plus PNG/PDF/ASE/JSON/CSS downloads, and by warning that archive anchors are evidence rather than recommended colours, which prevents a real misreading of the output.

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?

Front-loaded with what is returned, then examples, then the evidence-vs-recommendation caveat and the finalize handoff — a sensible ordering. The closing sentences about downloads and finalize are dense and slightly overlap the output schema, but each carries a distinct disambiguating point.

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 4-parameter evaluation tool with an output schema and readOnly annotations, the description supplies everything needed: input shape, verdict vocabulary, output composition, and the follow-up call. Minor gap is the absence of explicit guidance on when a sibling evaluator would be the better choice.

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%, so the baseline is 3. The description reinforces the 2-8 hex constraint and shows how use_case/market/medium combine in practice via worked examples, but adds no format or validation detail beyond what the schema already states.

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?

Opens with a specific verb+resource ('Evaluate a palette of 2-8 hex values') and immediately enumerates the outputs: verdict, score, per-colour roles, biggest weakness, and a fix suggestion. It also names the downstream companion palette_finalize with a clear division of labour, so the agent knows which tool finishes the job.

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?

Three concrete example briefs ('premium cushion collection UK ecommerce', 'hotel lobby interior', 'SaaS brand identity global digital') show the intended granularity of use_case/market/medium. The evaluate-then-finalize flow is spelled out. It stops short of saying when NOT to use this versus siblings like palette_audit or palette_compare, so it earns a 4 rather than 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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