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Local Llm Ops

Checked
bobmatnyc·vlatest·ai-ml·MIT

Provides LLMs guidance and assistance for building AI and machine learning applications.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add bobmatnyc/claude-mpm-skills --skill local-llm-ops -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

bobmatnyc

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned bobmatnyc/claude-mpm-skills at 718070a7d6.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
718070a7d6
Manifest
toolchains/ai/ops/local-llm-ops/SKILL.md
Scanned
2 files, 115 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill, Local LLM Ops (Ollama), provides a complete toolchain for running local Large Language Models (LLMs) on Apple Silicon devices. It includes setup scripts, command-line chat launchers, benchmarks, and diagnostic tools to manage the entire lifecycle of your LLM applications – from installation and model pulling to benchmarking performance. The skill streamlines the process of setting up and using LLMs locally, allowing for experimentation and development without relying on external services.

When to use it

  • You want to run Large Language Models (LLMs) locally on an Apple Silicon Mac.
  • You need a quick way to benchmark the performance of different LLM models.
  • You're encountering issues setting up or running your local LLM environment and require diagnostic assistance.
  • You want to experiment with different task modes like coding, creative writing, or analytical tasks using various LLMs.

Key capabilities

  • Automated Setup: Provides a setup_chatbot.sh script for easy installation and configuration of Ollama.
  • Chat Launchers: Offers multiple command-line chat launchers (chatllm, chat, chat.py) for interacting with LLMs.
  • Task Modes: Supports different task modes (coding, creative, analytical) using specific models like codellama:70b and llama3.1:70b.
  • Benchmarking: Includes a benchmark workflow (./scripts/run_benchmarks.sh) to evaluate LLM performance with configurable prompts and token limits.
  • Diagnostics: Provides a diagnostic script (./diagnose.sh) to troubleshoot setup issues.

Example prompts

  • ./chatllm - Launches the primary chat launcher for interacting with your local LLMs.
  • ./chat -t coding -m codellama:70b - Starts a chat session in "coding" mode using the codellama:70b model.
  • ./scripts/run_benchmarks.sh - Executes the benchmark script to measure LLM performance.

Tips & gotchas

  • Prerequisites: Requires Homebrew (brew) for installing Ollama and managing services.
  • Model Availability: You must pull at least one model (e.g., ollama pull mistral) before launching chat or benchmarks.
  • API Endpoint: The Ollama API runs on http://localhost:11434.