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name: quality-scaler description: "Routes QualityScaler tasks for Windows image and video upscaling, setup, and troubleshooting." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

QualityScaler

QualityScaler is a Windows-oriented image and video AI upscaler. Use this repo skill when a task mentions the app, its bundled model slots, its DirectML-backed runtime, or its image/video output naming and troubleshooting behavior.

Start here

• Read references/repo-provenance.md when you need to check whether this skill still matches the repository snapshot.
• Read references/shared-runtime-and-assets.md for the common Windows/runtime asset contract.
• Read references/shared-settings-and-output-contract.md for model names, supported formats, and output naming rules.
• Run scripts/inspect_qualityscaler_layout.py when you need a safe file-layout check before launch or import work.
• Run scripts/launch_qualityscaler.py when you want a preflight-gated way to start the GUI on a Windows machine.
• Run scripts/derive_qualityscaler_paths.py when you need to preview image, video, or frame output names without launching the GUI.

Route map

User intent	Go to
Install, launch, dependency, asset, or provider readiness	sub-skills/setup-runtime/SKILL.md
Still-image upscaling, model selection, tiling, metadata copy, or output naming	sub-skills/image-upscaling/SKILL.md
Video frame extraction, resume, encoding, codec fallback, or keep-frames behavior	sub-skills/video-upscaling/SKILL.md

Shared facts to keep in mind

• The repository is a single main Python file plus assets and model slots.
• The public runtime depends on Windows Tk/CustomTkinter, the DirectML ONNX provider, ffmpeg.exe, and exiftool.exe.
• The source module requires Python 3.12 or newer to import cleanly.
• The bundled launcher script can preflight the layout before attempting the GUI entrypoint.
• The app stores preferences in a versioned JSON file under the user's Documents folder.
• Image and video outputs follow the same suffix contract: model name, input resize, output resize, and optional blending tag.
• QualityScaler.py distinguishes image and video workflows by input extension, then dispatches into the image or video sub-skill paths.

How to use this skill

1. Start with setup-runtime when the app does not start, the provider is missing, or the asset layout is incomplete.
2. Use image-upscaling when the task is about still photos, alpha/grayscale handling, or output file naming for images.
3. Use video-upscaling when the task is about videos, resume logic, frame folders, or codec fallback.
4. If the problem is generic rather than workflow-specific, read references/troubleshooting.md first and then route to the owning sub-skill.

What not to do

• Do not assume Linux GUI runtime support for the app itself.
• Do not claim DirectML runtime verification unless the target system actually exposes it.
• Do not tell future agents to depend on the original repository checkout for runtime behavior; use the bundled references and scripts.
• Do not mix image-core and video-pipeline details into the root router when a sub-skill owns the workflow.

Useful bundled files

• references/source-map.md for the source-to-skill ownership map.
• references/troubleshooting.md for cross-cutting failure modes.
• scripts/inspect_qualityscaler_layout.py for layout checks.
• scripts/launch_qualityscaler.py for gated GUI startup.
• scripts/derive_qualityscaler_paths.py for output-name previews.

Minimal import sanity check

Before deeper inspection, confirm that the environment can parse the source with Python 3.12+ and that the expected runtime packages are available. If the environment is only for read-only inspection, use the bundled layout script and the shared references instead of trying to launch the GUI.