dmux-workflows

Manage parallel AI agent sessions with dmux across Claude Code, Codex, and OpenCode.

Updated Jun 22, 2026

Search Tags:#parallel processing #AI agent #parallel development #workflows #dmux

Ready to run

npx skills add https://github.com/TymorIbrahim/UniPilot --skill dmux-workflows-tymoribrahim

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dmux-workflows
Source: https://github.com/TymorIbrahim/UniPilot/tree/main/.cursor/.agents/skills/dmux-workflows
Command: npx skills add https://github.com/TymorIbrahim/UniPilot --skill dmux-workflows-tymoribrahim

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill solves the challenge of managing and coordinating multiple AI agent sessions in parallel, streamlining complex workflows across various AI tools.

Core Features & Use Cases

Parallel Agent Workflows: Orchestrate parallel sessions across Claude Code, Codex, OpenCode, and more.
Multi-Agent Development: Coordinate multi-agent development workflows for complex tasks.
Use Case: Imagine you are working on a large software project that requires research, implementation, and testing across multiple AI tools. This Skill allows you to run these tasks in parallel, significantly reducing development time.

Quick Start

Start a dmux session and create panes for each AI agent task you want to run in parallel. For example, to research a topic and implement a feature at the same time, you would create two panes: one for research and one for implementation.

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 for multiple development tasks?▼

You can run parallel AI agent sessions by using a tmux-based orchestration tool to create separate panes for each task. This allows you to execute research, implementation, and testing workflows simultaneously across different agents.

Can I coordinate multi-agent workflows across Claude Code and Codex?▼

Yes, multi-agent workflow coordination supports multiple harnesses including Claude Code, Codex, and OpenCode. You can orchestrate parallel sessions across these tools to streamline complex software engineering tasks.

What is the best way to manage parallel development with AI agents?▼

Managing parallel development with AI agents is best handled by orchestrating tmux sessions that divide tasks into dedicated panes. This approach coordinates complex multi-agent workflows and significantly reduces overall development time.

How do I start a dmux session to orchestrate parallel workflows?▼

To start a dmux session, create individual tmux panes for each AI agent task you want to run in parallel. For example, set up one pane for research and another for implementation to execute both simultaneously.

Do I need tmux to coordinate complex multi-agent workflows?▼

Yes, tmux is required as the underlying orchestration mechanism for managing parallel AI agent sessions. It provides the pane management needed to coordinate complex multi-agent workflows across various harnesses.

Why use tmux orchestration for parallel AI agent development?▼

Using tmux orchestration for parallel AI agent development solves the challenge of coordinating multiple sessions simultaneously. It streamlines complex workflows across various AI tools, significantly reducing development time for large software projects.