ollama

npx skills add Prism-Shadow/penguin-harness --skill ollama --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

# Ollama Serving Ollama runs open-weight models locally with automatic GPU detection and an OpenAI-compatible API on `http://localhost:11434`. ## Before you start If the user's message only invokes this skill (e.g. "use ollama skill") without a concrete request, ask the user what they want. Do not run any command until the goal is clear. Ask the user which model to run; if they have no preference, recommend the small default [Qwen/Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B) (`ollama pull qwen3.5:0.8b`). The model must fit the machine's RAM/VRAM. Ollama runs everywhere — macOS, Linux and Windows, on CPUs as well as NVIDIA/AMD GPUs — so engine choice follows the user's preference: Ollama is the simple default, while vLLM targets high-throughput GPU serving. Check the current state first: ```bash ollama --version # is Ollama installed? ollama ps # is the service already serving models? ``` If port 11434 is already serving, reuse that instance — never kill an existing Ollama process. ## Suggested workflow 1. Ask the user which model to run; with no preference, recommend [Qwen/Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B) (`qwen3.5:0.8b`). 2. Pick the engine the us

ollama --version   # is Ollama installed?
ollama ps          # is the service already serving models?
curl -fsSL https://ollama.com/install.sh | sh   # Linux; macOS/Windows use the desktop app
ollama pull qwen3.5:0.8b   # download a model
ollama run qwen3.5:0.8b    # interactive chat (pulls first if missing)
ollama list                # downloaded models
ollama ps                  # models loaded in memory
ollama stop qwen3.5:0.8b   # unload a model
curl http://localhost:11434/v1/models
ollama create qwen3.5-32k -f Modelfile