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generate_image

Generate AI images from text prompts, reference images, or video. Specify model, aspect ratio, and count for tailored results.

Instructions

Generate AI image

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesAI model/engine ID. Accepts both engine IDs and labels. Common models: flux.flux-realism, flux.flux-schnell, flux.flux-kontext-pro, google.gemini-2.5-flash-image, openai.imgen, recraft.recraft, stability.diffusion, bytedance.seedream-4
storageNo"asset" saves as a persistent TldrAsset (recommended — no expiry, visible in asset library). "transient" generates without saving to database (temporary URL, expires). "default" persists to AiImageArt gallery. asset
capabilityYesGeneration mode — NOT where the prompt text goes. The prompt text goes in parameters.prompt. Image capabilities: - "prompt" → text-to-image (most common; put your prompt in parameters.prompt) - "reference_image" → image-to-image (also requires parameters.reference_images) - "multiple_images" → batch generation - "first_last_frame" / "video_to_video" → video modes
parametersYesThe generation payload — what the AI model needs to produce the image. For capability=prompt: must contain prompt, aspect_ratio, and count. For capability=reference_image: also include reference_images array.
Behavior1/5

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

With no annotations, the description must disclose behavioral traits, but it only says 'Generate AI image'. It does not mention that the tool creates images via AI models, that results are temporary or stored, or any potential impacts like cost or usage limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise but lacks structure. It is a single phrase with no additional sentences. While conciseness is good, the description could be expanded to include key context without being verbose.

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

Completeness1/5

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

Given the tool's complexity (nested parameters, enums, no output schema, no annotations), the description is critically incomplete. It fails to summarize what the tool does, how it differs from related tools, or what the generation entails.

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 baseline is 3. The description adds no extra meaning beyond the schema's parameter descriptions. It does not help clarify parameter usage beyond what is already in the schema.

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

Purpose3/5

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

The description 'Generate AI image' is a clear verb+noun indicating image generation, but it is too brief and does not differentiate from sibling tools like text_to_video or generative_fill. The schema and name help, but the description alone lacks specificity.

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

Usage Guidelines1/5

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

No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives such as generative_fill, remove_background, or other image generation tools. There is no context on prerequisites or exclusions.

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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