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Rd Api Txt2Img

rd_api_txt2img

Turn text prompts into pixel-art images through the Retrodiffusion cloud API. Control style, size, seed, and more for tailored results.

Instructions

Retrodiffusion.ai cloud API: text to image (needs an API key: arg, RD_API_KEY env, or the extension's settings rdapikey).

Input Schema

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

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It usefully reveals that this is a remote cloud API call and that an API key is required, but it does not mention potential costs, rate limits, network dependence, output format, or side effects such as saving images.

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 front-loaded sentence with no filler. It states the core action, the service context, and the critical authentication requirement efficiently.

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?

Given 16 parameters, no output schema, no annotations, and no parameter documentation, the description is materially incomplete. It provides some useful context about the cloud API and auth, but an agent cannot confidently determine parameter meanings or expected return behavior.

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 does not compensate. It mentions API key sources, which helps slightly for the api_key parameter, but none of the 16 parameters—prompt, style, strength, rembg, save_grid, palette_url, etc.—are explained, leaving an agent with little guidance for correct invocation.

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 tool performs text-to-image generation via the Retrodiffusion.ai cloud API. It is clear enough to distinguish from image-to-image tools like rd_api_img2img, though it does not explicitly differentiate from similar text-to-image siblings like rd_cn_txt2img or rd_generate.

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?

No guidance is given about when to use this tool versus alternatives such as rd_generate, rd_cn_txt2img, or other local generation tools. The only operational note is the API key requirement, which is an authentication detail rather than usage direction.

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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