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Rd Api Img2Img

rd_api_img2img

Transform existing images into pixel art or other styles using the Retrodiffusion cloud API. Provide image paths and a prompt to produce AI-generated variations with control over style, size, and strength.

Instructions

Retrodiffusion.ai cloud API: image to image (needs an API key).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
rembgNo
styleNopixel art
widthNo
heightNo
promptYes
tile_xNo
tile_yNo
api_keyNo
strengthNo
save_gridNo
generationsNo
image_pathsYes
palette_urlNo
return_imageNo
palette_filesNo
save_progressNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does state that this is a cloud API and that an API key is needed, which is useful contextual information. However, it does not describe whether it writes files, returns images, requires network access, incurs costs, or what happens on failure.

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

Conciseness3/5

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

The description is a single sentence with no filler, making it concise in form. However, it is under-specified for a tool with 17 parameters and no other structured documentation. It is short rather than appropriately sized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 17-parameter API tool with no output schema, no annotations, and 0% schema description coverage, this one-line description is completely inadequate. An agent cannot determine required input semantics, output behavior, or how to use the tool correctly. The only useful fact is the API-key requirement.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds no meaning for the 17 parameters. The only hinted behavior, needing an API key, merely names the api_key parameter already present in the schema. None of the core parameters such as image_paths, prompt, strength, width, height, or generations are explained.

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 identifies the tool as a Retrodiffusion.ai cloud API operation and specifies the image-to-image task. It also notes the API-key requirement, which helps distinguish it from local or non-API image tools. It lacks an explicit verb like 'generates' or 'transforms,' but the purpose is still reasonably clear.

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 guidance on when to prefer this tool over alternatives such as rd_api_txt2img, rd_img2img, or rd_cn_img2img. It mentions that an API key is required, but does not explain prerequisites, expected input format, or when the cloud API should be used instead of local generation tools.

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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