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aaddyy_nano_banana_2

Generate images from text prompts with varied aspect ratios and multiple outputs. Use it to create custom visuals for content, design, or concept art.

Instructions

Google's state-of-the-art fast text-to-image generation model. Create stunning images from text prompts with support for extreme aspect ratios and multiple outputs. (~55 credits)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
promptYes
sync_modeNo
num_imagesNo
aspect_ratioNo
output_formatNo
safety_toleranceNo
limit_generationsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses cost (~55 credits) and that multiple outputs and extreme aspect ratios are supported, but says nothing about safety filtering, sync vs async behavior, output format/return shape, or any limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

Three short sentences, front-loaded with the core capability and no filler. It is well sized, though the second sentence leans on marketing adjectives ('stunning') that consume space without adding operational meaning.

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?

A generation tool with 8 undocumented parameters, no annotations, and no output schema leaves the agent guessing about formats, defaults, and return values. Cost is the only genuinely helpful contextual detail supplied.

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?

All 8 parameters have 0% schema description coverage, so the description must compensate and largely does not. It loosely touches three parameters (prompt, aspect_ratio, num_images) but leaves seed, sync_mode, output_format, safety_tolerance, and limit_generations completely undefined, including their accepted value formats.

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?

States a specific verb and resource ('text-to-image generation model', 'Create stunning images from text prompts'), which is unambiguous. However, it never differentiates itself from close siblings such as aaddyy_nano_banana, aaddyy_image_generator, or aaddyy_ghibli_generator, so the agent cannot tell why this variant exists.

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 gives no when-to-use or when-not-to-use guidance and names no alternatives, despite several overlapping image-generation siblings. Only the implicit framing ('text-to-image') hints at context, and the credit note is pricing, not routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.