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imaginpro
by imaginpro

Generate Image

generate-image

Create AI-generated images from text descriptions using ImaginePro's API. Convert detailed prompts into visual content with support for tracking and notifications.

Instructions

Generate an AI image from a text prompt using ImaginePro

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDetailed description of the image to generate
refNoOptional reference ID for tracking
webhookOverrideNoOptional webhook URL for async notifications

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
successYes
imageUrlNo
messageIdNo
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the core action ('Generate an AI image') but lacks details on permissions, rate limits, costs, async behavior (implied by 'webhookOverride' but not explained), or output format. For a generative tool with potential side effects, this is a significant gap in transparency.

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 a single, efficient sentence: 'Generate an AI image from a text prompt using ImaginePro.' It's front-loaded with the core purpose, has zero waste, and is appropriately sized for the tool's complexity. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (which handles return values), 100% schema coverage for inputs, and no annotations, the description is minimally adequate. However, it lacks context on behavioral traits (e.g., async processing, costs) and sibling differentiation, making it incomplete for optimal agent use despite the structured data support.

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 description coverage is 100%, so the schema already documents all three parameters ('prompt', 'ref', 'webhookOverride') with clear descriptions. The description adds no additional semantic context beyond implying the tool uses a 'text prompt,' which is redundant with the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Generate an AI image from a text prompt using ImaginePro.' It specifies the verb ('Generate'), resource ('AI image'), and mechanism ('from a text prompt using ImaginePro'). However, it doesn't explicitly differentiate from siblings like 'gemini-imagine' or 'create-variant,' which might offer similar functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'gemini-imagine' (possibly another image generator), 'create-variant' (for modifying images), and 'reroll-image' (for regenerating), there's no indication of when this specific tool is preferred or what distinguishes it from others in the server.

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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