Colour Memory

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

Ecommerce Product Copy from Archive Colour

ecommerce_copy

Read-only

Generate complete ecommerce product copy for any colour. Input: hex + product type + tone + channel. Output: colour name, product title, short description, long description, SEO title, meta description, alt text, Instagram caption, and cross-sell suggestion. Every piece of copy is grounded in archive provenance -- never generic AI colour copy. The colour name comes from the nearest archive match, not invented. Examples: velvet cushion in Murex Luxury, ceramic vase in Woad Vat Blue, linen throw in Standlake Silt. Directly useful for Shopify, WooCommerce, and editorial product pages.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`hex`	Yes	Hex colour of the product e.g. '#4A2A50'
`tone`	No	Copy tone e.g. 'premium but not pompous', 'warm and accessible', 'heritage and serious'	premium but not pompous
`channel`	No	Sales channel e.g. 'shopify', 'etsy', 'instagram', 'editorial'	shopify
`brand_name`	No	Optional brand name to include in copy
`product_type`	Yes	Product type e.g. 'velvet cushion', 'ceramic vase', 'linen throw', 'candle'

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.2/5.0

Behavior4/5

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

Annotations declare readOnlyHint=true, and the description adds meaningful behavioral context: copy is grounded in archive provenance, colour names come from the nearest archive match rather than being invented. This goes beyond the annotation by explaining the underlying data source and generation philosophy, providing useful transparency about the tool's behaviour.

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 compact and information-dense, covering what it does, inputs, outputs, unique value, examples, and use cases in a single paragraph. Every sentence adds value, and the most important action is stated first. It avoids unnecessary fluff.

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?

The description provides a thorough overview of the tool's purpose, inputs, outputs, examples, and applicability. Given the output schema exists and there are no complex side effects or destructive actions, the description is nearly complete. It could mention edge cases like unavailable archive matches, but that is not essential for basic usage.

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 parameter purposes through examples (velvet cushion, ceramic vase, linen throw) and mentions the input combination (hex + product type + tone + channel). It does not add significant new semantic detail beyond what the schema already documents, but the examples provide practical context.

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 generates complete ecommerce product copy from a hex colour, listing specific inputs and outputs. It distinguishes itself from sibling tools like ecommerce_namer by covering full copy (titles, descriptions, SEO, social) rather than just naming.

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?

It gives clear context for use ('Directly useful for Shopify, WooCommerce, and editorial product pages'), implying suitable scenarios. However, it does not explicitly exclude alternatives or state when not to use this tool versus other colour/copy tools.

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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