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Product Line Colour Namer

ecommerce_namer
Read-only

Generate archive-grounded colour names for up to 40 product SKUs. Input: list of hex values, product category, brand name, naming style. Output: for each hex -- archive name, source citation, one-line product description, dE2000 match distance, match quality, and confidence score. Every name is archive-sourced, not invented. Each carries a primary source citation that can be defended to buyers, press, and brand teams. Use for paint ranges, candle collections, fashion lines, homeware, cosmetics. Style options: geographical, poetic, material, literary, mixed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hexesYesList of hex values e.g. ['#D4A829', '#1A5C6E']
styleNogeographical | poetic | material | literary | mixed (default)
max_dENoMax dE2000 distance to accept (default 25)
brand_nameNoBrand name for context
product_categoryNoe.g. 'paint', 'candle', 'fashion', 'homeware'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.1/5.0
Behavior4/5

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

Annotations provide readOnlyHint=true, so safety is already declared. The description adds meaningful behavioral context: every name is 'archive-sourced, not invented' and carries a defensible citation. It also states the 40-SKU limit. These go 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.

Conciseness4/5

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

The description is compact and front-loaded with the core action. It covers input, output, and use cases in a few sentences. The redundancy between 'Every name is archive-sourced, not invented' and the following citation sentence is minor but slightly bloats the text.

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?

For a tool with 5 parameters, an output schema, and read-only annotations, the description is complete: it states the input types, output format, use cases, and quality guarantees. It does not explain the behaviour of max_dE, but the schema describes it, so the gap is acceptable.

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% and parameter descriptions are self-sufficient. The description repeats some parameter names (hexes, style, brand, category) and mentions style options already in the schema, but adds no new meaning beyond the schema. Baseline 3 applies because the schema does the heavy lifting.

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+resource+constraint: 'Generate archive-grounded colour names for up to 40 product SKUs.' It clearly distinguishes from siblings like colour_namer by emphasizing 'archive-grounded' and the ecommerce context, and it enumerates the exact output fields.

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 explicitly names target use cases ('Use for paint ranges, candle collections, fashion lines, homeware, cosmetics'), giving clear context. However, it does not state when to avoid this tool or name alternatives such as colour_namer, so it lacks the when-not/exclusion guidance for 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

A3.7/5.0
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