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Break a Colour Cliche

archive_cliche
Read-only

Subvert expected colour associations for any concept. Searches colour archives for contradictions and generates memorable one-liners, short stories, and tweets for brand storytelling.

Instructions

Find the most surprising archive colour for a concept and generate a memorable one-liner subverting the obvious expectation. Supply a concept (e.g. 'love', 'grief', 'luxury', 'power') and optionally the expected colour (e.g. 'red' for love). The archive finds the contradiction and Claude writes the one-liner, short story, and tweet. Example: love + red returns Shakespeare's dark green with 'Love is not red. It is the green of someone still waiting in a field.' Use this for public-facing demos, content, and brand storytelling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conceptYesColour concept to subvert e.g. 'love', 'grief', 'luxury', 'betrayal', 'power'
expected_colourNoOptional: the cliche colour to contradict e.g. 'red', '#FF0000'. Hex or colour name.
n_resultsNoNumber of archive entries to search (default 8)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
resultNo
errorNo
Behavior4/5

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

Annotations indicate readOnlyHint=true, and the description adds context about searching an archive and generating content via Claude. It discloses the tool's behavior without contradiction, though it could mention that no data is mutated.

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 concise, with two paragraphs front-loading the purpose and an example. Every sentence contributes meaning, though it could be slightly more compact.

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?

Given the output schema exists, the description's coverage of the tool's input and output (one-liner, short story, tweet) is adequate. It omits edge cases but is sufficient for typical creative use.

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 schema has 100% coverage, and the description adds value by explaining how parameters work together (e.g., concept and expected_colour) with examples. This goes beyond the schema's basic 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 clearly states the tool's purpose: find the most surprising archive colour for a concept and generate a memorable one-liner subverting expectations. It uses specific verbs and resources, and the unique focus on subverting clichés distinguishes it from sibling tools like colour_story or colour_strategy.

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 usage context: public-facing demos, content, and brand storytelling. It includes an example but does not explicitly state when not to use or compare to alternatives, though the context is sufficient for most agents.

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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