Create a new image from a reference image and text prompt, using the reference to guide style, subject, or composition.
Generate an image based on a reference image and text prompt.
| Name | Required | Description | Default |
|---|---|---|---|
| seed | No | ||
| prompt | Yes | ||
| strength | No | ||
| image_url | Yes | ||
| model_name | No | ||
| guidance_scale | No | ||
| negative_prompt | No | ||
| num_inference_steps | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden, and it says nothing about cost, latency, determinism via seed, how 'strength' alters fidelity to the reference, or safety filtering. For a generation tool that returns a new artifact, this is a substantial gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no wasted words, but the brevity reflects under-specification rather than tight editing. Concise in form, thin in substance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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, but for an 8-parameter generation tool with no annotations and 0% schema coverage, the description leaves tuning parameters and sibling selection entirely unspecified. Inadequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% across 8 parameters, so the description must compensate and does not. It only gestures at image_url and prompt; strength, guidance_scale, seed, negative_prompt, num_inference_steps, and model_name are left entirely undefined in both places.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and output ('Generate an image') conditioned on two named inputs ('reference image and text prompt'). This distinguishes it in spirit from generate_image (text-only) and edit_image, but it never names or contrasts those siblings explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use guidance at all. With siblings generate_image, edit_image, and generate_image_batch available, an agent gets no criteria for choosing reference-image generation over plain text-to-image or editing. The reference-image condition is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.