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generate_image

Create images from text descriptions using Stable Diffusion technology. Configure performance settings, aspect ratios, and select from hundreds of styles to generate custom visuals.

Instructions

Generate an image using Fooocus Stable Diffusion API.

Args:
    prompt: Text description of the image to generate
    performance: Performance setting (Speed, Quality, Extreme Speed)
    custom_styles: Comma-separated list of custom styles (optional, will auto-select if not provided)
    aspect_ratio: Image aspect ratio (default: 1024*1024)

Returns:
    Dictionary containing generation result with image URLs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
performanceNoSpeed
custom_stylesNo
aspect_ratioNo1024*1024

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions the API and return format but lacks critical behavioral details: no information on rate limits, authentication needs, error handling, or what happens if generation fails. For a generative tool with zero annotation coverage, this is insufficient.

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

Conciseness4/5

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

The description is well-structured with sections for Args and Returns, making it easy to scan. It's concise with no wasted sentences, though it could be more front-loaded by emphasizing the core purpose first.

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's complexity (image generation with 4 parameters) and no annotations, the description is moderately complete. It covers parameters and return format, but lacks behavioral context and usage guidelines. The output schema exists, so describing return values isn't needed, but other gaps remain.

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 0%, so the description must compensate. It lists all 4 parameters with brief explanations (e.g., 'Text description of the image to generate' for prompt), adding meaning beyond the schema's titles. However, it doesn't fully detail constraints like valid aspect ratio formats or performance options, leaving gaps.

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 image using Fooocus Stable Diffusion API.' It specifies the verb ('Generate') and resource ('image'), though it doesn't explicitly differentiate from sibling tools like list_available_styles. The purpose is specific but lacks sibling comparison.

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?

No guidance is provided on when to use this tool versus alternatives. The description mentions the API but doesn't specify scenarios, prerequisites, or exclusions. It's a basic functional statement without usage context.

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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