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text_to_image

Turn text prompts into images by creating a Grok Imagine task on RunAPI. Returns task ID, status, and output URLs for generated images.

Instructions

Create a Grok Imagine task on RunAPI (text to image). Returns a task id, status, and output URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
waitNoPoll until the task reaches a terminal status.
modelNoRunAPI model slug for this model line.
promptYesImage generation prompt.
enable_proNoEnable Pro image generation mode.
timeout_msNo
aspect_ratioNoOutput aspect ratio.
callback_urlNoWebhook URL for terminal Task delivery.
poll_interval_msNo
enable_safety_checkerNoEnable content safety checks.
Behavior3/5

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

The description adds some behavioral context by stating 'Returns a task id, status, and output URLs', giving a clue about async task behavior. However, with no annotations, it does not disclose async semantics, polling details, side effects, or required permissions. This is modest but incomplete transparency.

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 a single sentence with no fluff, front-loaded with the action verb 'Create'. Every word adds value, balancing purpose and return information efficiently.

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?

The tool has 9 parameters, no output schema, and no annotations, making it moderately complex. The description only covers the basic purpose and rough return shape, but fails to explain when to use wait vs callback_url, how to integrate with get_task, what terminal statuses look like, or any prerequisites. This is insufficient for confident invocation.

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

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 78% (7 of 9 params have descriptions), just below the 80% high threshold. The description adds no parameter semantics; notably, timeout_ms and poll_interval_ms are undocumented in both schema and description, leaving important behavioral knobs unexplained. The description fails to compensate for this gap.

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 explicitly states 'Create a Grok Imagine task on RunAPI (text to image)' with a specific verb and resource, and the parenthetical clarifies the exact operation. This distinguishes it from sibling tools like edit_image, upscale_image, and text_to_video. It also mentions the return format, reinforcing purpose.

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 when-to-use or when-not-to-use guidance is provided. The description does not mention alternatives, exclusions, or context like 'Use this to generate images from text prompts'. An agent would have to infer usage solely from the tool name and the generic description, which is not explicit.

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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