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Complete Colour Strategy

colour_strategy
Read-only

Evaluate a hex colour's brand fit, market risk, category cliches, material behaviour, copy hooks, and usage rules across multiple markets and mediums.

Instructions

The flagship commercial endpoint. Combines archive grounding, verdict, brand fit, market risk, category cliche check, material behaviour, copy hooks, and usage rules in a single call. Input: hex + brand_context (category, positioning, audience, channels) + constraints (avoid, must_work_on) + markets + medium. Output: verdict, strategy summary, archive anchor, commercial signal, category cliche risk level, market reading per market, material notes, usage rules (primary use, secondary use, avoid, pair_with), copy hooks (one_liner, social, brand_rationale), and alternatives. Examples: luxury fragrance brand UK/France/Japan, heritage interior specification, premium ecommerce packaging, SaaS brand identity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hexYesHex colour to evaluate e.g. '#4A2A50'
brand_contextNoBrand context object
constraintsNoConstraints object
marketsNoTarget markets e.g. ['UK', 'France', 'Japan']
mediumNoPrimary medium e.g. 'packaging', 'interior', 'digital'general

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
resultNo
errorNo
Behavior4/5

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

Annotations already indicate readOnlyHint=true; the description adds valuable context about the tool's scope and outputs, enhancing transparency beyond the annotation.

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 well-structured, starting with purpose, then listing inputs and outputs, and ending with examples. Every sentence is informative and necessary.

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?

The description thoroughly covers the tool's purpose, all inputs with examples, and expected outputs. Given the complexity and presence of an output schema, it is fully complete.

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?

The description adds meaning by grouping inputs (hex, brand_context, constraints, markets, medium) and providing examples, which goes beyond the schema's individual 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 explicitly states it is the 'flagship commercial endpoint' that combines multiple analyses (archive, verdict, brand fit, etc.), clearly distinguishing it from sibling tools like colour_verdict or colour_cultural_risk.

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 context for when to use this tool (for a comprehensive strategy), but does not explicitly state when not to use it or list alternative 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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