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aaddyy_upscale_image

Upscale and enhance images via Topaz AI up to 4x, with face enhancement, denoising, and sharpening.

Instructions

Upscale and enhance images using the powerful Topaz AI model. Supports face enhancement, denoising, sharpening, and generative upscaling up to 4x. (~12 credits)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNo
detailNo
promptNo
denoiseNo
sharpenNo
textureNo
strengthNo
image_urlYes
autopromptNo
creativityNo
crop_to_fillNo
output_formatNo
upscale_factorNo
fix_compressionNo
face_enhancementNo
subject_detectionNo
face_enhancement_strengthNo
face_enhancement_creativityNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

C2.8/5.0
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 disclosure burden. It usefully surfaces the credit cost, but says nothing about whether the original image is preserved, what permissions or URL accessibility are required, expected latency, output format defaults, or failure modes for an 18-parameter generative operation.

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?

Three short sentences, capability-first, with the cost caveat appended. Every sentence carries information and nothing is padded.

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?

For an 18-parameter tool with zero schema documentation, no annotations, and no output schema, the description is far too thin. An agent cannot know which of the many optional knobs to set, what values are legal, or what it will get back.

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

Parameters2/5

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

Schema description coverage is 0% across 18 parameters, so the description must compensate and largely does not. It mentions a few features that loosely map to face_enhancement, denoise, sharpen and upscale_factor, but leaves model, detail, prompt, texture, strength, creativity, crop_to_fill, output_format, autoprompt and others entirely unexplained.

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 verb and resource ('Upscale and enhance images') plus the underlying model (Topaz AI), and enumerates the capabilities (face enhancement, denoising, sharpening, 4x upscaling). It is clearly distinct in intent from siblings like background_remover or image_compressor, though it never names an alternative to route against.

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, no statement of prerequisites (e.g. that image_url must be publicly reachable), and no comparison to sibling image tools such as image_generator or image_compressor. The only decision-relevant detail is the implicit cost note (~12 credits).

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