A remote execution engine for managing Ollama task queues and automated code generation via SSH.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ollama-task-orchestrator
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install ollama-task-orchestrator using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Ollama Task Orchestrator?
The Ollama Task Orchestrator is a specialized tool designed to bridge the gap between local development environments and remote high-performance worker machines. As part of the Openclaw Skills ecosystem, it enables developers to offload intensive LLM tasks—such as code generation and test execution—to a remote server running Ollama.
This skill provides a robust management layer over standard SSH connections, offering exclusivity locking to prevent task collisions and deep health monitoring of the Ollama server. By utilizing Openclaw Skills like this orchestrator, developers can leverage powerful models like qwen2.5-coder:32b without taxing their local hardware, maintaining a fluid and responsive coding experience.
Ollama Task Orchestrator Use Cases
- Offloading heavy LLM inference to a dedicated remote GPU worker.
- Automating remote code generation and direct file writing via SSH.
- Managing shared AI compute resources with queue locking and health checks.
- Executing remote test suites and shell commands within a unified AI agent workflow.
How Ollama Task Orchestrator Works
- The Openclaw agent initiates a command which is routed through the skill entry point.
- The skill establishes a secure SSH connection to the configured OLLAMA_WORKER_HOST.
- A locking mechanism checks for active tasks to ensure exclusive access to the remote Ollama instance.
- The runner scripts on the worker machine interface with the Ollama API to process code generation or system tasks.
- Results, such as generated code or test outputs, are streamed back to the local environment and the lock is released.
Ollama Task Orchestrator Setup
To integrate this into your Openclaw Skills environment, ensure your SSH alias is configured in your ~/.ssh/config and follow these steps:
# Define environment variables
export OLLAMA_WORKER_HOST="your-worker-alias"
export OLLAMA_RUNNER_PATH="~/worker/runner"
# Initialize the worker directory structure
mkdir -p ~/worker/projects
# Check the connection and queue status
ollama status
Ollama Task Orchestrator Data Schema & Taxonomy
The skill maintains a structured hierarchy on the worker machine to ensure persistent project contexts and clean execution paths:
| Path | Description |
|---|---|
WORKER_ROOT |
The base directory for all operations (default: $HOME/worker) |
PROJECTS_DIR |
Contains individual subdirectories for different codebases |
runner/ |
Stores the shell scripts (queue_status.sh, run_task.sh) responsible for logic execution |
skill.py |
The local entry point that maps Openclaw commands to remote actions |
Ollama Task Orchestrator Advanced Features
- Stale Lock Recovery: Automatically or manually clear execution locks if a process hangs.
- Server Management: Ability to kill and restart the remote Ollama service directly through the CLI.
- Custom Model Routing: Toggle between different LLM models by updating the OLLAMA_MODEL configuration.
- Context-Aware Execution: Set a DEFAULT_PROJECT to automatically scope code generation and testing tasks.
SKILL.md
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