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    Image Upscaler :

    1

    Three enhancement tiers, 4K enlargement, and interactive before/after comparison.

    $5

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    Image Upscaler :

    Image Upscaler :

    Example session with this skill installed

    Use Image Upscaler on the attached photo of my two cats. Show me Light Cleanup, Standard Enhancement, and Detail Reconstruction so I can compare the different strengths.

    Keep the cats recognizable and retain their pose, framing, gray and white coat colors, and the blanket pattern as closely as the model allows. Focus on fur, whiskers, eye clarity, and fabric texture without adding objects or changing the scene.

    Provide a before/after comparison and export the Standard Enhancement version to a 3840px long edge. Resampling is allowed. Report the actual input and output dimensions and label the delivery method.

    • Read your context and instructions
    • Compiled the image upscaler

    Two cats, three enhancement strengths

    Illustrative walkthrough using the actual cat images shown in this listing's screenshots. The original is a soft photo of two cats resting together on a patterned blanket. The three generated versions let you compare enhancement strength before choosing a result.

    VersionEnhancement approachWhat to inspect
    Light CleanupGentle cleanup and restrained detail enhancement.Fur edges, whiskers, and whether the softer appearance suits the photo.
    Standard EnhancementStronger clarity and texture enhancement.Eye detail, coat texture, and the blanket pattern.
    Detail ReconstructionMore assertive reconstruction of fine texture.Plausible added detail and any changes to the cats' features or fabric.

    Delivered example

    • Three generated cat-image variants, shown in the gallery in the order above.
    • A before/after viewer with a draggable Compare divider, a side-by-side view, Fit and 100% inspection, and a Download image control.
    • Enhancement candidates shown in the gallery: original 1024 × 769; each generated result 1447 × 1087.
    • Standard Enhancement 4K export: 3840 × 2885, resampled with Lanczos from 1447 × 1087. The input file is retained; this is not native model-generated 4K. The gallery screenshots show the enhancement candidates before this export.
    • A small aspect-ratio difference is disclosed in the viewer; edges may not align exactly.

    Choose your result

    Start with Light Cleanup for a restrained appearance, then compare Standard Enhancement for more definition. Inspect Detail Reconstruction closely before choosing it: reconstructed fur or fabric texture is a plausible AI interpretation, not verified recovery of the original detail.

    Use the divider to inspect the cats' eyes, noses, whiskers, and blanket pattern. Check at 100% and download the version you prefer. Exact identity, geometry, and pattern preservation are not guaranteed.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Enhance images with Light Cleanup, Standard Enhancement, or Detail Reconstruction. Choose how much detail may change, with content presets for portraits, products, illustrations, and gradients to guide preservation of composition, identity, text, and visual style.

    Export images to 4K with a 3840px long edge while keeping their aspect ratio. Use native model output when available, or enlarge a smaller result with the included Lanczos resampling helper. Resize-only requests can enlarge an existing image without AI redrawing. The workflow keeps original files and records the actual delivery method.

    The skill includes a portable before/after viewer with Compare, side-by-side, Fit, 100% inspection, and download of the supplied result without further processing. Python helpers check dimensions, aspect ratio, hashes, and native-output or export-record consistency.

    Gallery order: Light Cleanup, Standard Enhancement, Detail Reconstruction. The screenshots show the interactive before/after viewer using actual generated examples.

    Resampling increases pixel dimensions; it does not recover verified missing detail. Native generation and preservation quality depend on the connected image provider and tool. Explicit native-only requests remain subject to native-output verification. Detail Reconstruction can synthesize plausible fine texture in approved noncritical areas.

    Designed for Codex with an image-generation or editing tool. The local 4K exporter, verification, and comparison helpers require Python 3 and Pillow.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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    Python

    Listed15 days ago

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