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Found 196 Skills
Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.
Use when a migration is already known to stay on the LangGraph orchestration side, including stages, routing, checkpoints, interrupts, persistence, streaming, and subgraph boundaries.
Analyze codebases from the bottom up and generate a hierarchical README.md document tree. Start analysis from leaf directories, generate README.md files for each directory containing one-sentence descriptions of files, classes, and functions, and summarize layer by layer upwards to form a complete codebase documentation system. Supports state persistence and resumable analysis, suitable for scenarios such as understanding new projects, generating technical documentation, and analyzing code structures. Use this skill when you need to understand codebase structures, analyze function implementations, or generate code documentation.
Expert iOS development skill covering SwiftUI, UIKit, Core Data, App Store guidelines, and performance optimization. Use this skill when building, reviewing, or debugging iOS apps - views, navigation, data persistence, animations, or submission preparation. Triggers on SwiftUI layout and state management, UIKit view controller lifecycle, Core Data model design and migrations, App Store Review Guidelines compliance, memory and rendering performance profiling, and Swift concurrency patterns for iOS.
Implements Syncfusion React TreeGrid for hierarchical data with sorting, filtering, editing, exporting, paging, virtual scrolling, and advanced features. Supports configuration, CRUD, aggregates, templates, state persistence, and performance optimization in React applications.
Implement Syncfusion WPF DocumentContainer (Tabbed MDI Form) control for creating MDI and TDI interfaces. Use this skill when working with DocumentContainer, Multiple Document Interface (MDI), Tabbed Document Interface (TDI), or Visual Studio-style document management. Covers document windows, tab groups, window switchers, state persistence for document layouts, and dockable document windows in WPF applications.
Implements the Syncfusion WPF DockingManager control for Visual Studio-like docking interfaces with MDI/TDI support, floating windows, and auto-hide panels. Use this when creating docking layouts, window management systems, tabbed document interfaces, or IDE-style layouts in WPF applications. Covers dock panels, floating windows, auto-hide functionality, state persistence, and window management.
Expert knowledge for Azure Cache for Redis development including troubleshooting, best practices, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when configuring geo-replication, persistence, VNet/Private Link, CLI/PowerShell automation, or Blob import/export, and other Azure Cache for Redis related development tasks. Not for Azure Managed Redis (use azure-managed-redis), Azure HPC Cache (use azure-hpc-cache), Azure Blob Storage (use azure-blob-storage), Azure Table Storage (use azure-table-storage).
Expert knowledge for Azure Managed Redis development including troubleshooting, best practices, decision making, security, configuration, integrations & coding patterns, and deployment. Use when using Entra auth, geo-replication, persistence, Private Link, or ARM/Bicep deployments for Azure Managed Redis, and other Azure Managed Redis related development tasks. Not for Azure Cache for Redis (use azure-cache-redis), Azure Cosmos DB (use azure-cosmos-db), Azure Table Storage (use azure-table-storage).
Use when you need data access with Quarkus Hibernate ORM Panache — including PanacheEntity / PanacheEntityBase, PanacheRepository, named and HQL queries, DTO projections (project(Class)), pagination (Page.of()), N+1 avoidance (JOIN FETCH), optimistic locking (@Version / OptimisticLockException), @NamedQuery for validated reusable queries, transactions, @TestTransaction for test isolation, and immutable-friendly patterns. This is the Quarkus analogue to Spring Data for relational persistence. Part of the skills-for-java project
Implement Syncfusion Blazor Query Builder component for building dynamic, customizable query interfaces with complex filtering logic. Use this when creating advanced search interfaces, implementing business rule engines, or building data filtering workflows with nested condition groups and AND/OR logic. Supports rule management, drag-drop UI, state persistence, and extensive customization options.
Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.