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image.generate

Generate images with Gemini AI, save them to disk, and retrieve structured metadata. Supports custom dimensions, transparency settings, and reference images for guided editing.

Instructions

Generate an image with Gemini using a Google AI Studio API key. Saves the result to disk and returns structured metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNo
modelNo
widthNo
heightNo
promptYes
backgroundNo
output_dirNo
filename_hintNo
transparency_modeNo
reference_image_pathsNo
transparency_thresholdNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
modelYes
widthNo
heightNo
providerYes
warningsYes
mime_typeYes
transparencyNo
prompt_summaryYes
Behavior4/5

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

Since no annotations are provided, the description carries the full burden of disclosing side effects. It transparently states that the tool requires a Google AI Studio API key, saves the result to disk, and returns structured metadata. However, it does not mention potential overwrite behavior, network usage, or error conditions, which would enhance 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 concise at two sentences, front-loaded with the primary action 'Generate an image', and provides key behavioral context (API key, disk save, metadata) without unnecessary detail.

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 11 parameters, no annotations, and only a minimal description, the context is incomplete. While an output schema exists to explain return values, the description lacks parameter semantics, usage guidance, and deeper behavioral specifics, making it insufficient for a tool of this complexity.

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

Parameters1/5

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

The input schema has 11 parameters with 0% description coverage, and the tool description does not explain any of them. The description only mentions generating an image and saving to disk, leaving all parameter details ambiguous. This is a significant gap that the description fails to compensate for.

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 generates an image with Gemini, distinguishing it from the sibling image.edit by using the verb 'Generate' versus 'edit'. It also mentions saving to disk and returning metadata, which gives a clear purpose.

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 implies usage for generating new images, but it does not explicitly contrast with the sibling image.edit or provide when-not-to-use guidance. It mentions an API key requirement, which is helpful context, but lacks explicit alternative selection criteria.

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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