Colour Memory

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 -- show them to the customer. Never present the archive anchors a colour was derived from as the colours you are recommending. If you go on to choose a final palette OF YOUR OWN from this evidence, call palette_finalize once with those exact colours so the customer can see and download what you actually recommended.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`market`	No	Optional: target market e.g. 'UK', 'Japan', 'global'
`medium`	No	Application medium e.g. 'interior', 'digital', 'fashion', 'print'	general
`palette`	Yes	List of 2-8 hex values e.g. ['#31559B', '#E8D898', '#4A2A50']
`use_case`	Yes	What the palette will be used for e.g. 'luxury cushion collection', 'brand identity'

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

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

First observedJun 10, 2026

TDQS

A4.5/5.0

Behavior5/5

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

The readOnlyHint annotation is consistent, and the description adds valuable behavioral detail: the result already carries rendered palette downloads, users should show them, archive anchors must not be presented as recommended colours, and final recommendations should route through palette_finalize. This goes well beyond what annotations convey.

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 dense but every sentence earns its place: core behavior, output details, examples, download behavior, an important warning, and a routing instruction. It is front-loaded with what the tool does and structured so an agent can act on it without re-reading.

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?

For a tool with an output schema and a read-only annotation, this description is remarkably complete. It covers input constraints, illustrative use cases, result contents, presentation guidance, a safety warning, and the correct follow-up tool call, leaving no critical ambiguity for an agent.

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 description coverage is 100%, so the schema already documents palette, use_case, market, and medium. The description reinforces these semantics with context and examples, but does not add meaning beyond the schema, so the baseline of 3 is appropriate.

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?

States a specific verb ('evaluate') and resource ('a palette of 2-8 hex values'), and enumerates concrete outputs: a verdict, a score, colour roles, biggest weakness, and a suggestion. This clearly differentiates it from adjacent tools like palette_analyse or palette_compare, since none promise this specific verdict format.

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 conveys when the tool applies ('Evaluate a palette... for a use case, market, and medium') and gives realistic examples. It also gives explicit downstream routing: call palette_finalize once if you choose a final palette of your own. It does not name alternative comparison/analysis tools or exclusion conditions, so it stops short of 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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TDQS

A3.6/5.0

Disambiguation2/5

Several tool clusters perform near-identical functions: extract_image_colours, image_palette and palette_extract all extract dominant colours from images; colour_passport, colour_dna, colour_metrics and colour_cultural_risk all profile a single hex; and at least six compound 'complete package' tools (agent_brief, archive_report_brief, brand_report, design_session, image_brief, session_brief) overlap heavily in scope. The descriptions try to differentiate -- some even point to tool_guide for routing -- but the volume and similarity of clusters makes misselection likely.

Naming Consistency4/5

The vast majority of tools follow a clear domain_prefix_suffix pattern (colour_, palette_, archive_, brand_, accessibility_, project_) and within families naming is very disciplined (brand_guideline_specify/select/pdf/claims/status, project_get/list/versions/delete). However, a handful of outliers invert the order (extract_image_colours, ingest_image, render_colour_result, query_hex) and some descriptions reference tools that don't exist as endpoints (palette_from_concept, match_paint_system, get_colour_metrics).

Tool Count1/5

88 tools is far beyond any reasonable single-server surface, even for a platform spanning archives, branding, interiors and accessibility. The sheer number forces agents into a massive decision space, and many tools exist purely as convenience wrappers that replace chains of 3-6 other tools, suggesting aggressive consolidation was needed.

Completeness4/5

The surface covers an unusually broad domain -- archive search, colour science, palettes, branding, interiors, accessibility, image extraction, projects, and PDF/Word/Excel exports -- with very few dead ends for end-user workflows. Minor gaps: several compound-tool descriptions reference tools that no longer exist, and valid archive names are only discoverable via error messages rather than a dedicated listing endpoint.

Resources

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