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zellij

Remote-control zellij sessions for interactive CLIs by sending keystrokes and scraping pane output.

Why use this skill?

Automate interactive terminal workflows with the Zellij skill for OpenClaw. Manage persistent sessions, run REPLs, and execute parallel shell tasks with full TTY control.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/jivvei/zellij
Or

What This Skill Does

The zellij skill enables the OpenClaw AI agent to manage, control, and interact with persistent terminal environments. By leveraging Zellij—a modern terminal workspace—this skill allows agents to spawn interactive sessions, execute shell commands, manage multiple panes, and scrape output from remote processes. Unlike background execution, zellij provides a TTY-like experience, making it perfect for running interactive REPLs, monitoring long-running CLI tools, or orchestrating parallel coding agents that require a stable workspace across multiple turns.

Installation

To integrate this skill, use the ClawHub package manager. Ensure your system (macOS or Linux) has the zellij binary installed and present in your system PATH. Install via command: clawhub install openclaw/skills/skills/jivvei/zellij. Once installed, you can configure the data directory using the CLAWDBOT_ZELLIJ_DATA_DIR environment variable to ensure session persistence across agent restarts.

Use Cases

  • Interactive Coding: Running multi-turn coding sessions where the agent needs to maintain state in a terminal, such as debugging in a Python REPL or watching logs in real-time.
  • Parallel Task Orchestration: Launching multiple agent instances simultaneously to perform work across different project directories without cross-contamination.
  • Long-Running CLI Monitoring: Keeping a terminal session active with tools that require interactive inputs or frequent status checks, allowing the agent to 'attach' and 'detach' as needed.
  • Complex CLI Automation: Automating sequences that involve multiple steps within a terminal buffer, where the agent must read the visual output before issuing subsequent keystrokes.

Example Prompts

  1. "Start a new zellij session named 'data-processor' and open a python3 REPL in the first pane."
  2. "Check the current zellij sessions; if 'agent-2' is running, send a 'Ctrl+C' to stop the current process and run 'ls -la' to see the directory contents."
  3. "Attach to the 'python-dev' session and scrape the last 50 lines of output from pane 0 to summarize the current debugging logs."

Tips & Limitations

  • Safety & Persistence: Always use a designated data directory to prevent session clutter. Zellij keeps state in this directory, so consider it a workspace database.
  • Terminal Constraints: This skill requires a TTY-enabled environment. For simple non-interactive scripts that don't need persistent monitoring, prefer the standard exec tool to minimize system overhead.
  • Window Support: The skill is exclusive to macOS and Linux. Users on Windows should utilize WSL2 with the zellij binary installed within the Linux subsystem.
  • Output Handling: When using pipe to capture output, ensure your pattern-matching scripts (wait-for-text.sh) are correctly configured to avoid hanging the agent if the expected prompt never appears.

Metadata

Author@jivvei
Stars1947
Views1
Updated2026-03-04
View Author Profile
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-jivvei-zellij": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags(AI)

#terminal#automation#zellij#workflow#devops
Safety Score: 3/5

Flags: file-write, file-read, code-execution