Local Inference Tuning

Use this skill to design a local inference setup that fits the actual machine, model format, storage policy, and target workflow.

This skill may inspect hardware and local model inventory. Do not remove models, download large weights, change global package manager config, expose network services beyond loopback, or write to system-wide config unless the user explicitly approves.

Hardware Audit

Collect the minimum useful facts:

• OS and architecture;
• CPU / SoC / GPU;
• RAM or unified memory;
• available accelerators: Metal, CUDA, ROCm, Vulkan, CPU-only;
• free disk on the approved model/cache volume;
• thermal class if visible: desktop, laptop, fanless laptop;
• existing engines: Ollama, llama.cpp, MLX, vLLM, LM Studio, Docker;
• existing local models and formats: GGUF, MLX, safetensors, Ollama manifests.