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Verify AI Image Generation Colour Fidelity

agent_verify
Read-only

Verify if an AI-generated image matches the target colour palette from a brief. Returns a fidelity score, per-colour dE2000 distances, match quality, and overall verdict.

Instructions

Verify that an AI-generated image actually used the colours specified in an agent_brief call. Supply the generated image (URL or base64) and the target palette from agent_brief colour_tokens. Returns a fidelity score 0-100, dE2000 distance per colour, match quality per colour (accurate/acceptable/drifted/ignored), and an overall verdict. Use after agent_brief + image generation to close the colour loop.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
target_paletteYesHex values from agent_brief colour_tokens e.g. ['#ED9921', '#E29937']
image_urlNoURL of the generated image
image_base64NoBase64 encoded generated image

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
resultNo
errorNo
Behavior5/5

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

ReadOnlyHint annotation matches description. Description additionally details return metrics (fidelity score, dE2000, match quality, verdict), providing rich behavioral context beyond what annotations offer.

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?

Single paragraph, front-loaded with purpose, then usage, then output. Every sentence adds value with no redundancy.

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 3 parameters and an output schema, description covers all aspects: what it does, when to use, inputs, outputs, and workflow integration. No gaps.

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?

Schema has 100% coverage, but description adds meaning by linking target_palette to agent_brief colour_tokens and explaining image_url/image_base64 as alternatives. Also summarizes output, though output schema exists.

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?

Description uses specific verb 'verify' and resource 'colour fidelity', clearly distinguishing from sibling tools like colour_compare or palette_verdict. States exactly the inputs and outputs.

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?

Explicitly says 'Use after agent_brief + image generation to close the colour loop', giving clear context for when to invoke. Does not exclude alternatives or mention when not to use, but implied by the workflow.

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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