Manage Ollama models and run local LLM inference on Windows 10/11.
npx skills add https://github.com/IrisGoLab/PCClaw --skill win-ai-local
Please help me install this Agent Skill. Skill: win-ai-local Source: https://github.com/IrisGoLab/PCClaw/tree/main/skills/win-ai-local Command: npx skills add https://github.com/IrisGoLab/PCClaw --skill win-ai-local
Windows users who want to run large language models without cloud dependencies face latency, privacy concerns, and setup complexity. win-ai-local enables on-device LLM inference via Ollama, model management, and hardware detection to keep data local and responsive.
Install Ollama, start the Ollama server, and begin local LLM inference with a sample model.
High-intent search queries and answers about installing and using this skill.
Local LLM inference on Windows 10 or 11 is enabled via Ollama, which allows developers and power users to run on-device models. The Skill detects available hardware like NPU, GPU, and DirectML to accelerate offline inference and keep data private.
A dedicated GPU is not strictly required for on-device AI inference on Windows, as the Skill detects available hardware including NPUs, GPUs, and DirectML. It leverages whatever hardware is present to accelerate local model processing and reasoning.
To start and manage Ollama models locally, you can use provided commands to start and stop the Ollama server, as well as list and pull models. This allows you to download new models and run them entirely offline on your Windows machine.
The best way to keep LLM data private during Windows development is using offline local inference. By running models on-device via Ollama, no data leaves the machine, making it suitable for sensitive data and restricted networks without cloud dependencies.
Local LLM inference works completely without an internet connection once models are pulled. The Skill enables offline Windows workloads, ensuring on-device reasoning remains responsive and private even in restricted networks or completely disconnected environments.
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