Colour Memory

Historical Colour Evidence

historical_colour_query

Read-only

Ask a question about how historical colour authorities actually reasoned, and get evidence with provenance rather than a summary. Covers seven validated source builds -- Jennings (paint recipes, 1902), Bradley (rotating-disc apparatus, 1895), Vanderpoel (quantified object analyses, 1902), Beaumont (woven colour relationships), Hay (harmonic proportional powers, 1838), Guichard (measured spatial extents, 1880) and Hokusai (subject-conditioned colour application, 1848). Each answer names its source, its locator and what that kind of evidence CANNOT support. Use it for questions like 'how do I paint a leaf', 'what did Bradley's disc proportions measure', 'what's the difference between making a colour and applying it', or to check a claim someone has attributed to one of these authors. Crucially, these sources' numbers are NOT interchangeable: a recipe part, a disc share, an object percentage, a proportional power and a measured extent answer different questions, and the response says so explicitly rather than averaging them.

Input Schema

TableJSON Schema

Name	Required	Description
`mode`	No	'user' (default) returns an evidence-led answer packet with structured values retained. 'evidence' additionally returns the complete underlying records.
`query`	Yes	Plain-English historical colour question.
`sources`	No	Optional restriction to named sources.
`max_results`	No	Upper bound on evidence items (default 12).
`high_confidence_only`	No	Only high-confidence records.

Output Schema

TableJSON Schema

Name	Required	Description
`answer`	No	Evidence-led answer: what the evidence supports, one observation that changes the question where the records support one, and the boundary of the claim.
`evidence`	No
`do_not_say`	No
`incomparabilities`	No
`premise_correction`	No

TDQS

A4.7/5.0

Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses the provenance format, names the exact source builds, and explicitly warns that source numbers are not interchangeable and that the response will say so rather than averaging them. This is rich behavioral context that helps the agent anticipate outputs and limitations.

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?

Although the description is long, every sentence earns its place: main purpose, source inventory, provenance and limitation behavior, example queries, and a critical caveat. It is front-loaded with the purpose and well-structured for a domain-specific query tool.

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 rich output schema and annotations, the description covers all necessary selection and invocation context: what question to ask, which sources are involved, what the response will contain, and what it cannot do. No important aspect is missing for an agent to use the tool correctly.

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?

Input schema covers 100% of parameters, so baseline is 3. The description adds value by enumerating the seven source names and their evidence types, which directly informs the 'sources' parameter and helps shape a good query. It does not comment on mode, max_results, or high_confidence_only, but the schema already describes those.

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 phrase ('Ask a question about how historical colour authorities actually reasoned') and a clear deliverable ('evidence with provenance rather than a summary'). It differentiates itself from the many sibling colour tools by naming seven specific source builds and the exact use cases, such as checking claims attributed to these authors.

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 it for questions like...' examples and explains what the evidence can and cannot support. It does not name alternative tools or give explicit when-not-to-use conditions, but the context is clear enough to guide selection.

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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