3.6천건 · 관련도순
Clarify priority and emphasis by fixing unclear primary actions, competing visual weight, loud section titles, and weak label/value treatment. Use when the user mentions hierarchy, prioritization, too much competition, grayscale confusion, loud headings, or unclear primary actions.
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Improve layout composition, spacing systems, grouping, and visual rhythm. Use when the user mentions weak layout structure, arbitrary spacing, weak grouping, crowded composition, or layout monotony rather than priority/emphasis problems.
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Create standout, technically ambitious interfaces that feel extraordinary through cinematic transitions, advanced motion, heavy rendering, or other high-ambition implementation work. Use when the user wants to wow, impress, go all-out, or push a feature beyond conventional UI polish—not when simple visual confidence or routine cleanup is enough.
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Reduce visual intensity, saturation, and noise while preserving hierarchy and character. Use when the structure is basically sound but the design feels too loud, bold, garish, aggressive, or overstimulating—not when the real problem is structural clutter, too many features, or not enough personality.
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Simplify cluttered UI by removing unnecessary elements, choices, features, and structural complexity. Use when the problem is too many controls, options, features, or competing elements—not when the structure is sound and the real issue is only visual intensity or lack of personality.
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Improve how interfaces use photos, screenshots, icons, illustrations, and user-uploaded media so visuals support clarity instead of undermining it. Use when the user mentions images, screenshots, background photos, hero images, icon sizing, user-uploaded media, crops, overlays, or image readability.
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Before any PR that touches frontend, run the app and visually verify PT/EN pages on mobile and desktop. Use when finishing UI work or opening a frontend PR.
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Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.
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Pre-PR verification for VenTu — tests, data validation, static build, and e2e for the touched surface. Use before opening any PR. For visual UI checks also load ventu-verify-ui.
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Define or review a visual system, DESIGN.md, or redesign direction. Use for typography, layout, color, motion, and interaction design decisions.
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Build AI data analysis assistants with visualization. TRIGGERS - Use when user needs help with ai-data-analyst related tasks.
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Generate a visual KPI report card with a headline metric, secondary stats, and branding — shareable as an image.
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Draws debug overlays in a running CARLA world via world.debug — points, lines, arrows, bounding boxes, and text strings, each with a colour and lifetime. Use when the user asks to "draw/mark/highlight a point or box in the world", "visualise a path/waypoints", "label a location", or "show something on the map for debugging". Shapes are an overlay, not actors.
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Windows アプリ開発 (WinUI 3 / XAML) の UI 基盤リファレンス。 Grid, StackPanel, Canvas, RelativePanel, SplitView, ScrollViewer、x:Bind, x:Name, x:Class, StaticResource, ThemeResource、添付プロパティ, 依存関係プロパティ、Style, ControlTemplate, DataTemplate, VisualStateManager, ResourceDictionary、Acrylic, Mica, SystemBackdrop, SystemBackdropElement、compact sizing、Binding, INotifyPropertyChanged, ObservableCollection, IValueConverter, DataContext, MVVM、 Storyboard, DoubleAnimation, EasingFunction, ThemeTransition, ConnectedAnimation, ImplicitAnimation、XamlOptionalChanges。
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Windows アプリ開発 (DirectX / WinRT メディア) のグラフィックス・メディア API リファレンス。 Direct2D (ID2D1Factory, ID2D1DeviceContext, ID2D1Bitmap1, ID2D1Effect, D2D1 Effects, ID2D1PathGeometry), DirectWrite (IDWriteFactory, IDWriteTextLayout, DWriteCore), Direct3D 11/12 (D3D11CreateDevice, D3D11On12, DXGI SwapChain, HLSL, D3D12 PipelineState, D3D12 DRED), Microsoft.UI.Composition (Compositor, Visual, ExpressionAnimation, InteractionTracker, MicaController), カメラ・画面キャプチャ (MediaCapture, MediaFrameReader, GraphicsCaptureSession, Windows Studio Effects, OpenCV)、音声・動画再生 (MediaPlayer, MediaPlaybackSession, AudioGraph, MediaTranscoder, AdaptiveMediaSource, HLS, DASH, CastingDevicePicker, AudioPlaybackConnection)。
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CadQuery (Python 製 3D CAD スクリプティングライブラリ) リファレンス。 Workplane API (lineTo / extrude / revolve / sweep / loft / fillet / chamfer / shell)、 Sketch API、Assemblies (Constraint solver)、Free Function API (hollow / prism / draft / offset2D, History)、 Selectors、Shape / Vertex / Edge / Wire / Face / Shell / Solid、 Import / Export (STEP / DXF / STL / glTF / SVG)、Visualization (VTK, cadquery.fig 非ブロッキング, Jupyter)、CQGI。
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Bring the Unity Editor window to front. Use when Unity must be visible for visual checks or user-facing interaction.
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Capture Unity Editor windows or Game View rendering as PNG. Use for visual checks, debugging, documentation, or annotated UI element coordinates.
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Applies Innovations for Poverty Action's official brand colors and typography to any sort of artifact that may benefit from having IPA's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
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Design, implement, review, and audit Android Jetpack Compose UI/UX for phone interfaces. Use when a request concerns concrete Compose layout, components, interaction, accessibility, or visual behavior. Do not activate for framework or dependency presence alone; non-UI Android work is excluded.
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Renders Hi-C contact matrices honestly and reproducibly with matplotlib, cooltools, HiCExplorer, pyGenomeTracks, FAN-C, CoolBox, and plotgardener. Covers the raw/ICE-balanced/observed-over-expected transform choice, LogNorm vs symmetric-diverging colormaps with vmax/percentile clipping, resolution-to-feature matching (compartments 100-500kb, TADs 10-40kb, loops 5-10kb), square vs rotated-triangle track-stacking, NaN/white-stripe handling, virtual 4C, APA/saddle/on-diagonal pileups, two-condition side-by-side and log2-ratio maps, and interactive (HiGlass) vs scripted-static publication figures. Use when plotting a contact matrix, choosing a normalization or color scale, building a multi-track Hi-C figure, making a virtual 4C profile, piling up loops/boundaries, or comparing two conditions.
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Detects TAD boundaries from balanced Hi-C contact matrices via the diamond-window insulation score (cooltools insulation) and HiCExplorer hicFindTADs, returning a continuous log2 insulation track, valley-prominence boundary_strength, and Li/Otsu-thresholded is_boundary flags across a list of window sizes. Covers the multi-scale window sweep (sub-TAD to compartment-domain), why the boundary is reproducible but the domain partition is not, cross-condition comparison via differential SCORE not differential partition, and the insulation-vs-compartment orthogonality. Use when calling TADs or domain boundaries, computing insulation scores, choosing a window size, ranking boundary strength, comparing boundaries across conditions, or annotating CTCF-backed boundaries; route domain rendering to hic-visualization and boundary-feature overlap to genome-intervals.
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Unsupervised clustering and cell-type identification for high-dimensional flow, spectral, and mass cytometry - FlowSOM, PhenoGraph, FlowSOM-via-CATALYST, with UMAP/tSNE for visualization. Covers the type-vs-state marker distinction (cluster on lineage, test state within clusters), over-provision-then-metacluster, the Weber-Robinson benchmark, seed dependence and metacluster stability, why embeddings are for looking not measuring, and median-heatmap annotation/merging. Use when discovering populations without predefined gates, choosing a clustering algorithm, selecting the number of metaclusters, or annotating clusters into cell types.
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Handles batch effects in bulk RNA-seq via design-matrix inclusion (the correct path for DE), ComBat/ComBat-seq for visualization, SVA for unknown latent factors, RUVSeq for negative-control-gene-anchored unwanted variation, and limma::removeBatchEffect for plotting only. Encodes the Nygaard 2016 cardinal sin against testing on a batch-corrected matrix, the choice between SVA/RUVg/RUVs/RUVr, the confounding non-identifiability problem, the single-cell boundary (Harmony/MNN are NOT for bulk), and the Goh 2017 harmonization critique. Use when designing a DE analysis with batch structure, troubleshooting batch-dominated PCA, choosing ComBat vs ComBat-seq, handling unknown batch via SVA, integrating across studies, or deciding when (rarely) to subtract batch.
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