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Gemini Image Prompt Tool

gemini_image_prompt_tool
Read-only

Generate structured image generation prompts from a description, mood, and style to guide Gemini image creation and improve visual results.

Instructions

Help craft an effective image generation prompt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
moodNoDesired mood or atmosphere.
modelNoModel to use for prompt crafting.flash
styleNoDesired art style (photorealistic, cartoon, watercolor, etc).
descriptionYesWhat you want the image to show.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

C2.9/5.0
Behavior2/5

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

The annotation readOnlyHint=true already tells the agent this is a non-destructive operation, and the description adds nothing beyond that. It does not clarify whether the tool merely returns text for the agent to reuse in a generation call, which model the 'model' parameter selects, or how the crafted prompt is delivered.

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?

A single short sentence with no filler, and the core action is front-loaded. It is efficient, though arguably undersized for a tool with four parameters and a workflow role.

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?

An output schema exists, so return values need not be explained. The remaining gap is workflow context: the description never positions this relative to the many image-generation and image-edit siblings, nor indicates that its output feeds into them.

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 all four parameters (description, mood, style, model) are already documented in the schema, including defaults. The description adds no format hints or examples beyond the schema, so the baseline 3 applies.

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 action ('craft') on a specific artifact ('image generation prompt'), which is clearly distinguishable from the image-generating siblings like gemini_generate_image_tool and gemini_imagen_generate_tool. However, it never explicitly names or contrasts itself against those siblings, so differentiation is implicit rather than stated.

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?

There is no when-to-use guidance and no alternatives named. An agent cannot tell from the description whether this should be called before gemini_generate_image_tool, instead of it, or as a standalone helper. The relationship to the workflow siblings is left entirely to inference.

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