dmux-workflows

Orchestrate parallel AI agent sessions across dmux-enabled panes.

Updated Apr 4, 2026
One-click install
npx skills add https://github.com/mitul-bhatia/Vibes --skill dmux-workflows-mitul-bhatia
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dmux-workflows
Source: https://github.com/mitul-bhatia/Vibes/tree/main/.github/skills/dmux-workflows
Command: npx skills add https://github.com/mitul-bhatia/Vibes --skill dmux-workflows-mitul-bhatia

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Orchestrates the coordination and management of multiple AI agent sessions across dmux-enabled panes, reducing manual setup and context switching.

Core Features & Use Cases

  • Parallel orchestration: run agent prompts in separate panes and merge results efficiently.
  • Cross-harness collaboration: manage workflows across Claude Code, Codex, OpenCode, and other tools.
  • Pattern-driven workflows: support research+implement, multi-file features, test+fix, and cross-harness collaboration.

Quick Start

Start a dmux session and create multiple agent panes to run parallel workflows.

Frequently Asked Questions about dmux-workflows

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run parallel AI agent sessions in separate tmux panes?

To run parallel AI agent sessions, use dmux to orchestrate multiple tmux panes across harnesses, executing defined prompts concurrently and merging the results efficiently. This reduces manual context switching.

Can I manage AI workflows across different harnesses like Claude Code and Codex?

Managing AI workflows across different harnesses like Claude Code, Codex, and OpenCode is supported through cross-harness collaboration patterns, enabling split parallel work and consolidated results.

What do I need to set up before orchestrating dmux workflows?

Orchestrating dmux workflows requires a tmux-compatible environment, the dmux tool installed, and clearly defined prompts and workflows to execute across the parallel agent panes.

What are common workflow patterns for parallel AI agent orchestration?

Common workflow patterns for parallel AI agent orchestration include research and implementation, multi-file feature development, test and fix cycles, and cross-harness collaboration.

How does parallel orchestration reduce manual setup for AI agents?

Parallel orchestration reduces manual setup by automatically managing multiple AI agent sessions across dmux-enabled panes, eliminating the need to manually open tabs and switch contexts.

When should I use tmux for AI agent workflows instead of a single session?

Use tmux for AI agent workflows when you need to execute research, implementation, and testing phases concurrently across multiple panes to consolidate results faster than sequential execution.