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generate_image

Generate an image from a text prompt using AI. Saves the image to disk. Supports high or fast quality options.

Instructions

Generate a new image from a text description using Gemini AI. Returns the generated image and saves it to disk.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDetailed description of the image to generate
modelNoOptional model override for this request
qualityNoModel tier: "high" (best quality, default) or "fast" (cheaper/faster)
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool saves the image to disk, which is a key behavioral trait. However, it omits details like potential disk space impact, permission needs, or whether generation is synchronous or async.

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 extremely concise with two sentences, each adding value. The first sentence states the primary action, the second describes return and side effect. No superfluous text.

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

Completeness3/5

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

With 3 parameters and no output schema, the description should explain the return value more clearly. 'Returns the generated image' is vague—could be a URL, file path, or base64. The agent lacks information on what to expect as output, which is critical for tool 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 description coverage is 100%, so the schema already documents all parameters. The tool description adds 'from a text description' but that aligns with the prompt parameter. It does not add semantic value beyond what the schema provides, meeting the baseline.

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 generates a new image from text using Gemini AI. The verb 'Generate' and resource 'image' are specific. While it doesn't explicitly distinguish from sibling tools like 'edit_image' or 'generate_video', the combination of name and description makes the creation purpose clear.

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 provides no guidance on when to use this tool versus alternatives. It does not mention when not to use it or any prerequisites (e.g., API key required). The agent must infer usage from context.

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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