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create_image_task

Generates images asynchronously via APIAny. Submit a model and prompt; optionally specify size, quality, reference images, and callback URL. Requires paid confirmation.

Instructions

Create a paid APIAny asynchronous image generation task. Requires APIANY_API_KEY and confirm_paid_request=true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes
promptYes
sizeNoAspect ratio such as 1:1 or 16:9, or a pixel size when supported.
qualityNoResolution/quality tier such as 1k, 2k, 4k, standard, or hd.
image_urlsNoOptional reference/input images for image-to-image or editing.
callback_urlNoOptional public HTTPS callback URL.
extra_jsonNoOptional extra request fields to merge into the JSON body.
confirm_paid_requestNo
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that the task is asynchronous and requires a paid request, which adds behavioral context. However, it does not describe other important traits such as error handling, rate limits, idempotency, or what the response looks like.

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 a single sentence, which is concise, but contains a typo ('APIAny') that reduces clarity. It could be slightly restructured for better readability without adding length.

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

Completeness2/5

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

Given the tool has 8 parameters, nested objects, and no output schema, the description provides minimal context. It does not explain return values, error handling, or parameter interactions, leaving significant gaps for correct invocation.

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 coverage is 63% (baseline 3). The description adds value by specifying that 'confirm_paid_request' must be set to true, which goes beyond the schema's default of false. However, it does not explain other parameters like 'model', 'prompt', 'size', etc., leaving interpretation to the schema.

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 creates an 'asynchronous image generation task' with a 'paid' characteristic. However, the phrase 'paid APIAny' contains a typo that slightly obscures clarity. It does not explicitly distinguish itself from the sibling tool 'create_video_task', but the resource type (image vs. video) is implicitly different.

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?

The description mentions prerequisites (APIANY_API_KEY and confirm_paid_request=true) but provides no guidance on when to use this tool versus alternatives like 'create_video_task'. There are no explicit when-to-use or when-not-to-use instructions.

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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