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image_text_to_image

Convert text prompts into images using AI models. Returns generated image URLs with typical 24-hour validity.

Instructions

Generate images from a text prompt. Returns image URLs (typically valid 24h).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNo
seedNo
modelYesImage generation model id
widthNo
heightNo
promptYes
aspect_ratioNo
callback_urlNo
guidance_scaleNo
prompt_optimizerNo
Behavior2/5

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

No annotations are provided. The description only mentions that the tool returns image URLs valid for typically 24 hours. It does not disclose authentication needs, rate limits, destructive potential, or other behavioral traits. For a generation tool with 10 parameters, 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.

Conciseness5/5

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

The description is two sentences long, front-loaded with the core function, and contains no extraneous information. Every word serves a purpose.

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's complexity (10 parameters, no output schema, no annotations), the description is far from complete. It does not explain required vs optional parameters, return format details, or provide examples. A generation tool with many options needs more context.

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 only 10% (only 'model' has a description). The tool description does not explain any parameters, such as 'n', 'seed', 'width', 'height', or 'aspect_ratio'. It adds no meaning beyond the schema, which itself is sparse.

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 verb 'generate' and resource 'images from a text prompt', distinguishing it from the sibling 'image_to_image' which presumably uses an image input. This is specific and unambiguous.

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

Usage Guidelines3/5

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

The description provides no guidance on when to use this tool versus alternatives like 'image_to_image' or 'video_text_to_video'. It does not specify prerequisites, required parameters, or usage constraints beyond the prompt requirement.

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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