This is the comprehensive guide you need if you're shipping on-device AI on Apple platforms. It walks you through Foundation Models for zero-setup text generation and structured output with @Generable, Core ML for converting and optimizing custom models with quantization and Neural Engine deployment, MLX Swift for maximum throughput with open-source LLMs on Apple Silicon, and llama.cpp for cross-platform GGUF inference. The framework selection router at the top is genuinely helpful for cutting through the decision paralysis. Heavy on code examples for tool calling, streaming, session management, and availability checking. If you're building anything that runs AI locally on iPhone or Mac, this covers the entire stack.
npx -y skills add dpearson2699/swift-ios-skills --skill apple-on-device-ai --agent claude-codeInstalls into .claude/skills of the current project.
Select a file.
sickn33/antigravity-awesome-skills
wshobson/agents
kotlin/kotlin-agent-skills