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flux_generate_image

Generate AI images from a text prompt using multiple Flux models. Choose between speed and quality options for artwork or photos.

Instructions

Generate AI images from a text prompt using Flux.

Flux is a family of fast, high-quality image generation models by Black Forest Labs.
Different models offer different tradeoffs between speed, quality, and capabilities.

Use this when:
- You want to create new images from a text description
- You need high-quality AI-generated artwork or photos
- You want fast image generation with good prompt following

For editing existing images, use flux_edit_image instead.

Returns:
    Task ID and generated image information including URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the image to generate. Be descriptive about style, subject, lighting, and composition. Examples: 'A majestic mountain landscape at golden hour, photorealistic', 'Cyberpunk street scene with neon lights and rain, cinematic', 'Minimalist logo design of a phoenix, vector art style'
modelNoFlux model to use for generation. Options: - flux-dev: Fast development model, good balance of speed and quality (default) - flux-pro: Higher quality production model - flux-pro-1.1: Improved production model with better prompt following - flux-pro-1.1-ultra: Highest quality, supports aspect ratios instead of pixel sizes - flux-kontext-pro: Context-aware model for editing and style transfer - flux-kontext-max: Maximum context model for complex editing tasksflux-dev
sizeNoImage size. For flux-dev/pro/pro-1.1: pixel dimensions like '1024x1024' (256-1440px, multiples of 32). For flux-pro-1.1-ultra and kontext models: aspect ratios like '1:1', '16:9', '9:16', '4:3', '3:2', '2:3', '4:5', '5:4', '3:4', '21:9', '9:21'. Default varies by model.
countNoNumber of images to generate. Only supported for generate action. Default is 1.
callback_urlNoWebhook callback URL for asynchronous notifications. When provided, the API will POST to this URL when the image is generated.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It mentions that different models have tradeoffs and that a task ID is returned with image URLs, but it does not explicitly state that generation is asynchronous or estimate time/cost. The callback_url parameter hints at async but could be clearer.

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 concise and well-structured, starting with a clear one-liner, then background, use cases, alternative, and return info. Every sentence adds value without redundancy.

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 presence of an output schema (not shown), the description covers the main contextual points: what it does, when to use, alternative, and return format. It could benefit from more details on prerequisites or async behavior, but overall it is fairly 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 input schema has 100% description coverage, providing detailed explanations for each parameter. The description adds minimal value beyond the schema, such as mentioning model tradeoffs, but baseline 3 is appropriate since the schema already does the heavy lifting.

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 generates AI images from a text prompt using Flux, with a specific verb and resource. It distinguishes itself from the sibling tool flux_edit_image by mentioning that for editing, the other tool should be used.

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

Usage Guidelines5/5

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

The description includes a 'Use this when:' section with explicit bullet points outlining appropriate scenarios. It also directly states the alternative flux_edit_image for editing tasks, providing clear guidance on tool selection.

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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