Colour Memory

Search Colours by Concept or Culture

query_conceptual

Read-only

Ask a cultural, historical, or material colour question. Returns named archive colours with provenance and cultural context. Works for abstract queries like 'grief' (returns Ophelia Violet, Titan's Grief), 'toxic Victorian pigments' (returns Nightshade Poison Berry Purple, Victorian Arsenic Mirror Silver), or 'the sea at dusk' (returns Evening Sea, Thames Blue Dusk). Even a vague or personal-sounding query never comes back empty -- result_path in the response tells you honestly whether this was a 'direct' hit, a 'broadened' retry (relaxed match threshold), or a 'redirected' fallback (dropped an archive restriction or switched to full-corpus semantic search).

Input Schema

TableJSON Schema

Name	Required	Description
`query`	Yes	The colour concept or cultural question to search for
`archive`	No	Optional: restrict to a named archive e.g. 'Japan', 'Pigment', 'OttomanEmpire'
`n_results`	No	Number of results (default 5)

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.5/5.0

Behavior4/5

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

With readOnlyHint annotation already covering safety, the description adds valuable behavioral context: it discloses that even vague queries never return empty, and explains the result_path field honestly indicates direct, broadened, or redirected match types. This goes 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, each earning its place: main purpose, return details, examples, and the honest fallback behavior. No repetition of schema, no fluff, well front-loaded.

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?

With output schema present, the description needn't explain return structure. It explains the crucial result_path behavior, gives rich examples, and covers the main edge case (vague queries). Complete for the tool's complexity.

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 enriches query semantics with specific examples and reveals that the archive parameter can be dropped in the 'redirected' fallback, giving additional meaning beyond the schema's basic descriptions.

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 clearly states a specific verb ('Ask'), a resource ('cultural, historical, or material colour question'), and what it returns ('named archive colours with provenance and cultural context'). Concrete examples like 'grief' and 'toxic Victorian pigments' distinguish it from hex-based siblings like query_hex.

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 clear when-to-use context through examples of abstract, cultural, and vague queries. It implies these are the intended use cases but does not explicitly name alternatives or state exclusions, so it falls 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

A3.8/5.0

Disambiguation2/5

With 88 tools, there is substantial overlap: colour_passport vs colour_dna vs colour_metrics vs colour_cultural_risk are explicit components of the same object; palette_concept vs palette_strict vs palette_generate vs palette_heritage overlap heavily; and four image extraction tools exist (extract_image_colours, image_palette, palette_extact, ingest_image). Although descriptions are detailed and tool_guide exists, an agent will frequently struggle to select the correct tool unambiguously.

Naming Consistency5/5

Nearly all tools follow a consistent snake_case noun_verb or domain-prefixed pattern (colour_*, palette_*, brand_*, archive_*, project_*, accessibility_*). The naming is uniform and predictable, with no mixing of styles or verb conventions across the set.

Tool Count1/5

88 tools is an extreme count for an MCP server. Even honoring the broad domain, the rubric places 50+ at the extreme end, and the high overlap between compound and individual tools suggests many could be consolidated or exposed as sub-resources rather than top-level tools.

Completeness5/5

The tool surface covers the full colour lifecycle: lookup, analysis, palettes, brand systems, accessibility, image extraction, interior design, archival research, reports, PDF generation, and project management. Workflows have clear entry points and few dead ends, and the presence of compound tools further closes integration gaps.

Resources

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