Manage local Ollama models autonomously with health monitoring, automatic fallback, self-healing, and offline operation without internet dependency.
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Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install offline-llamaOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install offline-llamaβ οΈ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js β
Option 2: Manual install (no Node required)
Download the ZIP, extract it, and place the folder at the path below. Restart your agent to activate.
Install path
~/.claude/skills/offline-llama/π‘Extract and place the folder at the path above, then restart your agent.
Category
π»Developer & DevOpsPlatforms
What Offline Llama can do for your AI workflow
Local ollama models directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
One-command installation β no complex setup required
Combine with other skills to build powerful multi-step AI workflows
Try these prompts with your AI agent after installing Offline Llama
Help me get started with Offline Llama
Explains what Offline Llama does, walks through the setup, and runs a quick demo based on your current project
Use Offline Llama to manage local Ollama models autonomously with health monitoring, aut...
Invokes Offline Llama with the right parameters and returns the result directly in the conversation
What can I do with Offline Llama in my developer & devops workflow?
Lists the top use cases for Offline Llama, with example commands for each scenario
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Offline Llama extends your AI assistant with the ability to manage local Ollama models autonomously with health monitoring, automatic fallback, self-healing, and offline operation without internet dependency. Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly β and it will take care of the task end-to-end, using Offline Llama as its underlying capability.
Offline Llama works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) β an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install Offline Llama once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.
Getting started with Offline Llama takes about two minutes. Place the skill at `~/.claude/skills/offline-llama/` (personal, all projects) or `.claude/skills/offline-llama/` (project-specific), then restart your AI client. From that point, typing `/offline-llama` in any conversation activates it, or the AI will use it on its own when it detects a relevant request.
Offline Llama has 713 installs and is part of the growing Developer & DevOps skill ecosystem on DiscoverAISkills. The source code is open on GitHub β you can inspect it, contribute fixes, or fork it to adapt the skill for your specific setup. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.
Place the skill folder at ~/.claude/skills/offline-llama/ for personal use (all projects), or .claude/skills/offline-llama/ for project-specific use. Restart your AI client, then invoke with /offline-llama or let the AI discover it automatically.
Offline Llama supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
Offline Llama is free to install. Check the repository for licensing information.
Manage local Ollama models autonomously with health monitoring, automatic fallback, self-healing, and offline operation without internet dependency.
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