Colour Memory

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

Explain a Colour's Provenance

archive_provenance

Read-only

Explains the provenance of a named archive colour: documented fact vs computational derivation vs cultural interpretation, with confidence and citation format. This is one component of colour_passport, but also a standalone research tool for deep provenance work (museum, documentary, editorial). Use colour_passport for a general profile; call this directly for research workflows needing full source-chain detail.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`colour_name`	Yes	Name of the archive colour e.g. 'Love Idleness', 'Woad Vat Blue', 'Murex Luxury'

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?

Annotations include readOnlyHint: true, and the description aligns by using 'explains' without implying mutation. The description adds meaningful behavioral context by enumerating what the provenance categories are and that confidence and citation format are returned. It goes beyond the annotation but doesn't discuss potential delays or limitations, so a 4 is appropriate.

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, front-loaded with the core purpose, then immediately provides usage guidance. Every phrase earns its place with no fluff or repetition.

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 simple input (one string), the presence of an output schema, and readOnly annotation, the description is sufficient. It explains what the tool returns at a conceptual level, when to use it, and how it differs from the closest sibling, making it complete for the complexity involved.

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?

The single parameter 'colour_name' is fully described in the schema with examples, and the description repeats the notion of a 'named archive colour' without adding additional syntax or format details. Since schema coverage is 100%, the description adds marginal value here.

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 the tool explains provenance of an archive colour and specifies the types of provenance (documented fact vs computational derivation vs cultural interpretation) along with confidence and citation format. It also distinguishes this from the sibling tool colour_passport by positioning it as a standalone deep-research tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly tells when to use this tool versus the alternative: 'Use colour_passport for a general profile; call this directly for research workflows needing full source-chain detail.' It also names target use cases (museum, documentary, editorial), providing clear context.

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

A3.7/5.0

Disambiguation2/5

Multiple tool clusters have unclear boundaries: colour_passport, colour_dna, colour_metrics, and colour_cultural_risk overlap heavily; palette_extract, extract_image_colours, image_palette, and ingest_image cover similar image-colour extraction territory; and compound tools like design_session, image_brief, session_brief, and archive_report_brief duplicate chains of component tools. The descriptions are detailed and occasionally state 'use this instead of X', but an agent still faces many near-duplicate choices.

Naming Consistency3/5

Names are consistently snake_case and often use domain prefixes (colour_, palette_, archive_, brand_, accessibility_), but verb placement is mixed: some are verb_noun (extract_image_colours, query_hex, style_match), others are noun_verb (colour_dna, palette_generate, brand_audit), and a few standalone names (ui_states, tool_guide, meta_capabilities) don't fit either pattern. The convention is readable but not uniform.

Tool Count1/5

At 88 tools, this is far beyond the reasonable well-scoped range and exceeds the 50+ extreme mismatch threshold. Many tools are compound wrappers that consolidate chains of simpler tools, adding redundancy and cognitive load rather than genuine coverage.

Completeness5/5

For the apparent domain, the tool surface is extremely comprehensive: colour extraction, analysis, naming, accessibility, cultural/provenance research, palette generation, brand systems, interior design, ecommerce copy, image briefs, project lifecycle, exports, and diagnostic tools are all present. Persistent objects have list/get/versions/delete/export support, so there are no obvious dead ends.

Resources

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