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edit_image

Modify existing images using text prompts to add or remove elements, transfer styles, inpaint specific areas, or combine multiple images.

Instructions

Edit an existing image using text prompts. Supports:

  • Adding/removing elements

  • Style transfer

  • Inpainting (changing specific parts)

  • Combining multiple images

Provide the path to an existing image and describe the changes you want.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesDescription of the edit to make. Be specific about what to change and what to preserve.
image_pathYesPath to the input image file to edit.
modelNoThe model to use for editing.nano-banana
aspect_ratioNoOptional aspect ratio for the output image.
image_sizeNoThe resolution of the output (only for nano-banana-pro).1K
filenameNoOptional filename for the output image.
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions editing capabilities, it doesn't disclose important behavioral traits like whether edits are destructive to the original file, what permissions are needed, rate limits, output format, or error conditions. The description is insufficient for a mutation tool with zero annotation coverage.

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 efficiently structured with a clear opening sentence, bullet points for capabilities, and a practical usage instruction. Every sentence earns its place, and information is front-loaded with the core purpose stated first.

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?

For a complex image editing tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like file handling, error cases, or what the tool returns. While the schema covers parameters well, the overall context for proper tool invocation is insufficient.

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?

With 100% schema description coverage, the baseline is 3. The description adds some value by mentioning 'path to an existing image' (reinforcing image_path) and 'describe the changes you want' (reinforcing prompt), but doesn't provide additional semantic context beyond what's already well-documented in the schema descriptions.

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's purpose with specific verbs ('edit an existing image using text prompts') and distinguishes it from siblings by focusing on editing existing images rather than generating new ones (generate_image) or composing multiple images (compose_images). The bullet points provide concrete examples of editing capabilities.

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 for when to use this tool ('edit an existing image') and implies alternatives through sibling tool names, but doesn't explicitly state when NOT to use it or directly compare with compose_images/generate_image. The guidance is practical but lacks explicit exclusions.

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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