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mordor-forge

gemini-media-mcp

compose_images

Create new images by combining 1-3 reference images with text prompts for style and content guidance. Use this tool to generate AI images based on visual references and descriptive instructions.

Instructions

Compose a new image using 1-3 reference images and a text prompt for style/content guidance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesText description guiding the composition
referenceImagesYesPaths to 1-3 reference images for style/content guidance
modelNoModel tier: nb2 (default) or pro
aspectRatioNoAspect ratio for the output

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
filePathYes
modelYes
mimeTypeYes
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 burden of behavioral disclosure. It mentions the use of reference images and a prompt but lacks critical details: whether this is a read/write operation, potential side effects (e.g., resource consumption), authentication needs, rate limits, or output characteristics. For a tool with no annotations, this is a significant gap in transparency.

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 a single, efficient sentence that front-loads the core functionality. Every word earns its place by specifying key constraints (1-3 reference images) and the tool's purpose without redundancy or fluff. It's appropriately sized for the complexity.

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?

Given the tool's moderate complexity (4 parameters, no annotations, but with an output schema), the description is minimally adequate. It covers the basic operation but lacks context about when to use it, behavioral traits, or integration with siblings. The output schema reduces the need to explain return values, but more guidance would improve completeness.

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 fully documents all four parameters. The description adds minimal value beyond the schema—it implies the purpose of 'referenceImages' and 'prompt' but doesn't provide additional context like format examples or usage tips. This meets the baseline for high schema coverage.

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 action ('compose'), resource ('new image'), and key constraints ('using 1-3 reference images and a text prompt'). It distinguishes from siblings like 'generate_image' by specifying the use of reference images, though it doesn't explicitly contrast with all alternatives. The purpose is specific but could be more differentiated from similar tools.

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 like 'generate_image' or 'edit_image'. It states what the tool does but offers no context about appropriate scenarios, prerequisites, or exclusions. This leaves the agent without clear decision-making criteria.

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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