Secondary local LLM inference engine via llama.cpp. This skill should be used when running GGUF models directly, loading LoRA adapters for Kothar, benchmarking inference speed, or serving models via llama-server. Complements Ollama (which remains primary for RLAMA and general use).
Quickly install llama-cpp AI skill to your development environment via command line
Source: tdimino/claude-code-minoan.
Direct access to llama.cpp for faster inference, LoRA adapter loading, and benchmarking on Apple Silicon. Ollama remains primary for RLAMA and general use; llama.cpp is the power tool.
To avoid duplicating model files, resolve an Ollama model name to its GGUF blob path:
To start an OpenAI-compatible server (port 8081, avoids Ollama's 11434):
Secondary local LLM inference engine via llama.cpp. This skill should be used when running GGUF models directly, loading LoRA adapters for Kothar, benchmarking inference speed, or serving models via llama-server. Complements Ollama (which remains primary for RLAMA and general use). Source: tdimino/claude-code-minoan.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/tdimino/claude-code-minoan --skill llama-cppSecondary local LLM inference engine via llama.cpp. This skill should be used when running GGUF models directly, loading LoRA adapters for Kothar, benchmarking inference speed, or serving models via llama-server. Complements Ollama (which remains primary for RLAMA and general use). Source: tdimino/claude-code-minoan.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/tdimino/claude-code-minoan --skill llama-cpp Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/tdimino/claude-code-minoan