Skill Detail

Coordinate multi-machine terminal agent teams with AI Maestro

Use AI Maestro to supervise terminal-based agents across machines with persistent memory, agent-to-agent messaging, inboxes, and transfer workflows.

Developer ToolsMulti-Framework
Developer Tools Multi-Framework Published
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COPY SKILL INSTRUCTIONS (OPTIONAL)
npx skills add agentskillexchange/skills --skill coordinate-multi-machine-terminal-agent-teams-with-ai-maestro Copy
Uses the third-party skills CLI, not an ASE-owned installer. Check your agent’s compatibility. This copies instructions; complete the upstream tool setup below separately.
At a glance
Tools required
AI Maestro, Node.js 18 or newer, tmux, git, and one or more terminal-based AI agents such as Claude Code, Codex, Aider, Cursor, OpenClaw, Hermes, or Droid.
Install & setup
Install with curl -fsSL https://raw.githubusercontent.com/23blocks-OS/ai-maestro/main/scripts/remote-install.sh | sh on macOS, Linux, or Windows through WSL2. Then open the AI Maestro dashboard, register the agents and repositories you are authorized to operate, and use the dashboard, inbox, memory search, and AMP messaging to coordinate multi-agent work.
Author
23blocks
Publisher
Organization
Last updated
Oct 6, 2026
Quick brief

Use AI Maestro when an operator is running multiple terminal-based AI agents and needs a durable control surface instead of manually copying context between terminals, machines, and agent sessions. AI Maestro gives agents persistent memory, searchable code context, an inbox, agent-to-agent messaging through AMP, and a dashboard for watching and moving agents across hosts.

How it works

What this skill actually does

The repeatable workflow is concrete: install AI Maestro, connect terminal agents such as Claude Code, Codex, Aider, Cursor, OpenClaw, or similar tools, assign each agent owned repositories or responsibilities, use the dashboard and inbox to coordinate handoffs, and rely on memory search and messaging instead of ad hoc terminal juggling. Invoke it instead of using a single agent product normally when the work involves several standing agents that need coordination, cross-machine continuity, or direct collaboration. The scope boundary is operator orchestration for existing terminal agents; it is not a generic AI dashboard, model SDK, task runner, or hosted agent platform listing.