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submit_inpaint

Submit an image inpainting job and get a job ID instantly. Specify a mask, pipeline, and prompt to fill the masked area with new content without waiting.

Instructions

Submit an inpainting job without waiting. Returns the job ID for manual polling.

Args:
    pipeline: Pipeline to use — "sd15", "sdxl", or "illustrious"
    positive_prompt: Text prompt describing what to paint in the masked region
    model_checkpoint: Model checkpoint filename to use
    image_base64: Base64-encoded input image
    mask_base64: Base64-encoded mask image (white = inpaint region)
    negative_prompt: Negative prompt (things to avoid)
    steps: Number of inference steps (1-150)
    cfg_scale: Classifier-free guidance scale (1-30)
    seed: Random seed (-1 for random)
    scheduler: Noise scheduler name
    loras: Optional list of LoRA configs, each with "name" (str) and optional "strength" (float 0-1)
    custom_vae: Optional custom VAE checkpoint filename

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
lorasNo
stepsNo
pipelineYes
cfg_scaleNo
schedulerNoDPM++ 2M
custom_vaeNo
mask_base64Yes
image_base64Yes
negative_promptNo
positive_promptYes
model_checkpointYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It clearly states the async nature and return of a job ID, which is important. However, it does not mention potential failure modes, rate limits, or what happens if the job fails, leaving some behavioral gaps.

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 a clear opening sentence followed by a parameter list. It is reasonably concise given the 12 parameters, and the key behavioral point (async, returns job ID) is front-loaded. The parameter list is necessary and not padded with fluff.

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?

The description covers the essential aspects for an async job submission tool: what it does, the parameters, and the return value. It lacks details on error handling and job lifecycle, but given the output schema exists and the tool is part of a larger job system, the description is fairly complete for an agent to invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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 provides detailed explanations for each parameter, including the meaning of mask_base64 (white = inpaint region), the range for steps and cfg_scale, and the structure for loras. This adds significant value beyond the bare schema, though some parameters like scheduler and custom_vae are only named without further detail.

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 submits an inpainting job asynchronously and returns a job ID for polling. It distinguishes itself from synchronous alternatives like inpaint_image and submit_generate by emphasizing the non-blocking nature and manual polling requirement.

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

Usage Guidelines4/5

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

The description implies usage for asynchronous inpainting jobs and mentions manual polling, which guides the agent on when to use this tool versus waiting for results. However, it does not explicitly contrast with sibling tools like inpaint_image or submit_generate, nor does it state when not to use it.

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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