Agent skill

avalonia-viewmodels-zafiro

Optimal ViewModel and Wizard creation patterns for Avalonia using Zafiro and ReactiveUI.

Stars 23,776
Forks 2,298

Install this agent skill to your Project

npx add-skill https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/development/avalonia-viewmodels-zafiro

SKILL.md

Avalonia ViewModels with Zafiro

This skill provides a set of best practices and patterns for creating ViewModels, Wizards, and managing navigation in Avalonia applications, leveraging the power of ReactiveUI and the Zafiro toolkit.

Core Principles

  1. Functional-Reactive Approach: Use ReactiveUI (ReactiveObject, WhenAnyValue, etc.) to handle state and logic.
  2. Enhanced Commands: Utilize IEnhancedCommand for better command management, including progress reporting and name/text attributes.
  3. Wizard Pattern: Implement complex flows using SlimWizard and WizardBuilder for a declarative and maintainable approach.
  4. Automatic Section Discovery: Use the [Section] attribute to register and discover UI sections automatically.
  5. Clean Composition: map ViewModels to Views using DataTypeViewLocator and manage dependencies in the CompositionRoot.

Guides

  • ViewModels & Commands: Creating robust ViewModels and handling commands.
  • Wizards & Flows: Building multi-step wizards with SlimWizard.
  • Navigation & Sections: Managing navigation and section-based UIs.
  • Composition & Mapping: Best practices for View-ViewModel wiring and DI.

Example Reference

For real-world implementations, refer to the Angor project:

  • CreateProjectFlowV2.cs: Excellent example of complex Wizard building.
  • HomeViewModel.cs: Simple section ViewModel using functional-reactive commands.

Expand your agent's capabilities with these related and highly-rated skills.

davila7/claude-code-templates

verl-rl-training

Provides guidance for training LLMs with reinforcement learning using verl (Volcano Engine RL). Use when implementing RLHF, GRPO, PPO, or other RL algorithms for LLM post-training at scale with flexible infrastructure backends.

23,776 2,298
Explore
davila7/claude-code-templates

openrlhf-training

High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with distributed architecture and GPU resource sharing.

23,776 2,298
Explore
davila7/claude-code-templates

gguf-quantization

GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.

23,776 2,298
Explore
davila7/claude-code-templates

Claude Code Guide

Master guide for using Claude Code effectively. Includes configuration templates, prompting strategies "Thinking" keywords, debugging techniques, and best practices for interacting with the agent.

23,776 2,298
Explore
davila7/claude-code-templates

qdrant-vector-search

High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.

23,776 2,298
Explore
davila7/claude-code-templates

behavioral-modes

AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.

23,776 2,298
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results