Intel GPU AI Skills

Intel’s open-source gpu-ai-skills repository provides 20 agent skills designed to help AI coding agents set up, run, size, benchmark, profile, debug, and migrate Hugging Face workloads on Intel Arc and Arc Pro GPUs. The Apache-2.0 package supports tools including Claude Code, Copilot CLI, Cursor, Codex, Gemini CLI, and others, allowing users to describe goals in natural language rather than manually select commands or GPU settings. Its skills cover system readiness, model-type detection, PyTorch, vLLM-XPU, SGLang, and llama.cpp deployment, VRAM-fit calculations and configuration recommendations, performance benchmarking, kernel-level profiling, and staged CUDA-to-XPU migration assessments and execution. The project emphasizes pre-launch memory estimation, verified inference responses rather than successful server startup alone, and profiling to identify specific performance bottlenecks. An example migration of a PDF-to-podcast application replaced external inference APIs with a local OpenAI-compatible vLLM-XPU endpoint on four Arc Pro B70 GPUs while retaining the broader application flow. Each skill includes executable validation contracts covering activation, required actions, verification steps, and prohibited configurations, with reported testing on physical Intel hardware and installation support for multiple agent environments.

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