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Generar imagen (Nano Banana)

generate_image

Generate an image from a text prompt using Gemini 2.5 Flash Image. Returns the image in base64.

Instructions

Genera una imagen a partir de un prompt de texto usando Gemini 2.5 Flash Image (Nano Banana). Devuelve la imagen en base64.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescripción detallada de la imagen a generar.
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently states that the output is a base64-encoded image and specifies the model used. However, it does not disclose potential non-determinism, API costs, or any failure behavior. While the generation action is inherently non-destructive, the description is adequate but not rich in details, meriting a 3.

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 exceptionally concise, containing just two sentences. It front-loads the primary action ('Genera una imagen') and immediately provides the model and output format. Every word earns its place; no superfluous information, making it highly efficient for an agent to parse.

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

Completeness5/5

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

For a tool with a single parameter, no output schema, and no nested objects, the description is complete. It explains what the tool does, the input, the model, and the return format ('Devuelve la imagen en base64'). There is no ambiguity for this simple tool, and the description fully covers its context.

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?

The schema has 100% coverage for the single parameter (prompt), so the baseline is 3. The description adds no additional parameter semantics beyond what the schema already provides; it simply restates that the image is generated from a text prompt. No extra clarification about prompt formatting or constraints is offered.

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 from a text prompt, with a specific verb (genera), resource (imagen), and input (prompt de texto). It also identifies the underlying model (Gemini 2.5 Flash Image) and mentions the output format (base64), which distinguishes it from sibling tools like edit_image and compose_images that likely modify or compose existing images.

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

Usage Guidelines4/5

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

The description provides clear context on when to use the tool: when you need to generate an image from a text prompt. It does not explicitly mention alternatives or exclusions, but the sibling tool names (edit_image, compose_images) imply different use cases. Since it lacks explicit 'when not to use' guidance, it falls short of a 5 but meets the 'clear context' criterion.

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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