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Found 2,746 Skills
Implement and configure the Syncfusion Blazor TreeMap component (SfTreeMap) for hierarchical data visualization. Use this when working with treemaps, area-proportional visualizations, or heat-map-like block displays. This skill covers TreeMap setup, layout configuration, data binding, color mapping, drill-down navigation, and accessibility features.
Build interactive timeline components that display events and milestones sequentially. Use SfTimeline with alignment controls, custom items, and event handlers. This skill covers timeline configuration and customization for creating visual timelines in Blazor applications.
Implement Syncfusion Blazor Toolbar (SfToolbar) component for creating interactive command bars and toolbars. Use this when working with toolbars, command bars, or action bars with buttons and icons. This skill covers responsive toolbars with overflow handling, item configuration and alignment, keyboard navigation, accessibility features, and dynamic item management.
Implement Syncfusion Blazor Breadcrumb (SfBreadcrumb) control for hierarchical navigation. Use this when building breadcrumb trails, auto-generating items from URLs, or managing dynamic navigation sequences. This skill covers overflow modes, item templates, icon customization, and responsive layout configurations.
Implement Syncfusion Blazor DataForm component for creating dynamic, data-bound forms with validation and field management. Use this when building forms in Blazor with Syncfusion components, handling form validation, binding models, creating editable fields, or managing form events. This skill covers form layout customization, data binding, FormItems configuration, FormAutoGenerateItems setup, templates, events, and data annotation validation.
Implements the Syncfusion Blazor HeatMap Chart component for multi-dimensional data visualization using color-coded grids. Use this when working with heatmaps, data matrices, correlation displays, or bubble heatmap variants. This skill covers installation, data binding, axis configuration, color palettes, legends, tooltips, and accessibility features.
Implement Syncfusion React Linear Gauge for displaying measurements on a linear scale. Use this skill when users need temperature sensors, KPI indicators, progress gauges, or real-time monitoring dashboards. Covers axes configuration, pointer types, ranges, annotations, customization, animations, print/export, accessibility, and internationalization.
Implements the Syncfusion React 3D Circular Chart component for pie and donut chart visualization. Use this when users need 3D circular charts, data labels, legends, tooltips, or empty point handling. Guides through installation, configuration, customization, and troubleshooting of 3D Circular Charts in React applications.
Use when writing Unreal Engine C++ code involving UPROPERTY, UFUNCTION, UCLASS, TArray, TMap, delegates, FString, garbage collection, or smart pointers. Also use when the user asks about "UE C++", USTRUCT, UENUM, FName, FText, TObjectPtr, TWeakObjectPtr, UObject lifetime, UE_LOG, or UE subsystems. For module build configuration, see ue-module-build-system. For Actor/Component architecture, see ue-actor-component-architecture.
Expert in Docker, docker-compose, Dockerfile patterns, and container orchestration for NestJS and Next.js applications. Use this skill when users need Docker setup, containerization, or docker-compose configuration.
Refactor Spring Boot and Java code to improve maintainability, readability, and adherence to enterprise best practices. This skill transforms messy Spring Boot applications into clean, well-structured solutions following SOLID principles and Spring Boot 3.x conventions. It addresses fat controllers, improper transaction boundaries, field injection anti-patterns, and scattered configuration. Leverages Java 21+ features including record patterns, pattern matching for switch, virtual threads, and sequenced collections.
Debug Scikit-learn issues systematically. Use when encountering model errors like NotFittedError, shape mismatches between train and test data, NaN/infinity value errors, pipeline configuration issues, convergence warnings from optimizers, cross-validation failures due to class imbalance, data leakage causing suspiciously high scores, or preprocessing errors with ColumnTransformer and feature alignment.