local-llm-ops — Claude Code skill: local LLMs with Ollama
A skill for running local models through Ollama on Apple Silicon: bring up the service, pull models, start chat sessions and benchmarks.
npx skills add bobmatnyc/claude-mpm-skills --skill local-llm-ops -a claude-codeWhat local-llm-ops does
The skill lays out the whole path for local LLM work in the localLLM repo: install Ollama, start the service, initialize the virtualenv, pull models, then open a chat or run measurements. Two commands get you going — ./setup_chatbot.sh followed by ./chatllm. With no models on disk, ollama pull mistral fixes that.
Setup and diagnostic scripts ship alongside CLI chat launchers that take task modes, such as ./chat -t coding -m codellama:70b. Benchmarks live in scripts/run_benchmarks.sh and read benchmarks/prompts.yaml plus benchmarks/models.yaml. Running ./install_aliases.sh gives you llm, llm-code and llm-fast. The virtualenv sits in .venv, configs and sessions under ~/.localllm/, and the Ollama API answers on http://localhost:11434.
Nothing works until Ollama is installed and its service is up: brew install ollama, then brew services start ollama. Confirm it with curl http://localhost:11434/api/version. When setup breaks, ./diagnose.sh narrows it down; the usual culprits are ollama missing from PATH or zero pulled models.
What it helps with
- bring up Ollama and its service on Apple Silicon from scratch
- pull a model and start a terminal chat
- benchmark several models against a prompt set
- switch chat task modes for code, prose and analysis
- find out why setup fails using the diagnostic script
Example prompts for the agent
- Run
./setup_chatbot.shand start a local chat - Benchmark the models listed in
benchmarks/models.yaml - The chat is not responding — run
./diagnose.shand tell me what broke
How to install local-llm-ops
1Skills CLI (Vercel)
npx skills add bobmatnyc/claude-mpm-skills --skill local-llm-ops -a claude-code2Manually: put the files in place
~/.claude/skills/local-llm-ops/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/local-llm-ops/
1Skills CLI (Vercel)
npx skills add bobmatnyc/claude-mpm-skills --skill local-llm-ops -a codex2Manually: put the files in place
.agents/skills/local-llm-ops/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add bobmatnyc/claude-mpm-skills --skill local-llm-ops -a cursor2Manually: put the files in place
.cursor/skills/local-llm-ops/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install bobmatnyc/claude-mpm-skills local-llm-ops2Manually: put the files in place
.github/skills/local-llm-ops/SKILL.md1Skills CLI (Vercel)
npx skills add bobmatnyc/claude-mpm-skills --skill local-llm-ops -a gemini-cli2Platform CLI
gemini skills install https://github.com/bobmatnyc/claude-mpm-skills --path toolchains/ai/ops/local-llm-opsManually: put the files in place
.devin/skills/local-llm-ops/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add bobmatnyc/claude-mpm-skills --skill local-llm-ops -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about local-llm-ops
How do I install local-llm-ops in Claude Code?
Run npx skills add bobmatnyc/claude-mpm-skills --skill local-llm-ops -a claude-code; the skill file lands at ~/.claude/skills/local-llm-ops/SKILL.md.
What does local-llm-ops do?
It covers local LLM operations with Ollama: environment setup, service startup, model pulls, chat launchers, benchmarks and diagnostics.
What do I need before using it?
Ollama installed with the service running, and at least one model pulled — ollama pull mistral, for instance.
Source text
SKILL.md · MIT
---
name: local-llm-ops
description: Local LLM operations with Ollama on Apple Silicon, including setup, model pulls, chat launchers, benchmarks, and diagnostics.
user-invocable: false
disable-model-invocation: true
version: 1.0.0
category: toolchain
author: Claude MPM Team
license: MIT
progressive_disclosure:
entry_point:
summary: "Run local LLMs with Ollama: setup venv, start service, pull models, launch chat, benchmark, and diagnose."
when_to_use: "Operating local LLMs on macOS, running Ollama-based chat sessions, or benchmarking models for speed/latency."
quick_start: "1. ./setup_chatbot.sh 2. ./chatllm 3. ollama pull mistral (if no models)"
tags:
- llm
- ollama
- local
- benchmark
- chat
- ops
---
# Local LLM Ops (Ollama)
## Overview
Your `localLLM` repo provides a full local LLM toolchain on Apple Silicon: setup scripts, a rich CLI chat launcher, benchmarks, and diagnostics. The operational path is: install Ollama, ensure the service is running, initialize the venv, pull models, then launch chat or benchmarks.
## Quick Start
```bash
./setup_chatbot.sh
./chatllm
```
If no models are present:
```bash
ollama pull mistral
```
## Setup Checklist
1. Install Ollama: `brew install ollama`
2. Start the service: `brew services start ollama`
3. Run setup: `./setup_chatbot.sh`
4. Verify service: `curl http://localhost:11434/api/version`
## Chat Launchers
- `./chatllm` (primary launcher)
- `./chat` or `./chat.py` (alternate launchers)
- Aliases: `./install_aliases.sh` then `llm`, `llm-code`, `llm-fast`
Task modes:
```bash
./chat -t coding -m codellama:70b
./chat -t creative -m llama3.1:70b
./chat -t analytical
```
## Benchmark Workflow
Benchmarks are scripted in `scripts/run_benchmarks.sh`:
```bash
./scripts/run_benchmarks.sh
```
This runs `bench_ollama.py` with:
- `benchmarks/prompts.yaml`
- `benchmarks/models.yaml`
- Multiple runs and max token limits
## Diagnostics
Run the built-in diagnostic script when setup fails:
```bash
./diagnose.sh
```
Common fixes:
- Re-run `./setup_chatbot.sh`
- Ensure `ollama` is in PATH
- Pull at least one model: `ollama pull mistral`
## Operational Notes
- Virtualenv lives in `.venv`
- Chat configs and sessions live under `~/.localllm/`
- Ollama API runs at `http://localhost:11434`
## Related Skills
- `toolchains/universal/infrastructure/docker`
© Claude MPM Team · MIT · bobmatnyc/claude-mpm-skills