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Generate Image (Stability AI)

ai.image.generate
Read-onlyIdempotent

Generate images from text prompts with style presets, aspect ratios, and negative prompts. Returns base64 PNG data URI via Stability AI.

Instructions

⚡ ACTION: Generate images from text prompts using Stable Diffusion — supports style presets (anime, cinematic, pixel-art, photographic...), aspect ratios, negative prompts. Returns base64 PNG data URI. Powered by Stability AI

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesText prompt describing the image to generate (e.g. "a futuristic city at sunset, cyberpunk style, detailed")
negative_promptNoWhat to exclude from the image (e.g. "blurry, low quality, text, watermark")
aspect_ratioNoImage aspect ratio (default "1:1")
style_presetNoStyle preset to guide generation

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
Behavior4/5

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

Annotations (readOnlyHint=true, destructiveHint=false) indicate safe, idempotent behavior. The description adds behavioral context by specifying it returns a base64 PNG data URI and is powered by Stability AI, enhancing transparency beyond annotations.

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, well-structured sentence with no wasted words. It efficiently conveys action, capabilities, and output format.

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 tool's complexity and the presence of an output schema, the description covers the essential: action, key features, and output format. It lacks only minor details like default parameters or model version, but is largely complete.

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?

The schema has 100% coverage with descriptions for all 4 parameters. The description adds marginal value by exemplifying style presets and mentioning aspect ratios and negative prompts, but does not provide new semantics beyond the schema.

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 verb 'Generate images' and the resource 'text prompts using Stable Diffusion'. It lists specific capabilities (style presets, aspect ratios, negative prompts) and distinguishes this tool as an image generation tool among many other AI tools on the server.

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

Usage Guidelines3/5

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

The description implies usage for text-to-image generation but does not explicitly state when to use this tool over alternatives, nor provides exclusion criteria or when-not-to-use guidance.

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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