dmux-workflows: Design & UI for AI Agents | OpenAgentSkill

Overview

Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across OpenAI Codex, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.

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dmux Workflows

Orchestrate parallel AI agent sessions using dmux, a tmux pane manager for agent harnesses.

When to Activate

Running multiple agent sessions in parallel
Coordinating work across OpenAI Codex, Codex, and other harnesses
Complex tasks that benefit from divide-and-conquer parallelism
User says "run in parallel", "split this work", "use dmux", or "multi-agent"

What is dmux

dmux is a tmux-based orchestration tool that manages AI agent panes:

Press n to create a new pane with a prompt
Press m to merge pane output back to the main session
Supports: OpenAI Codex, Codex, OpenCode, Cline, Gemini, Qwen

Install: npm install -g dmux or see github.com/standardagents/dmux

Quick Start

# Start dmux session
dmux

# Create agent panes (press 'n' in dmux, then type prompt)
# Pane 1: "Implement the auth middleware in src/auth/"
# Pane 2: "Write tests for the user service"
# Pane 3: "Update API documentation"

# Each pane runs its own agent session
# Press 'm' to merge results back

Workflow Patterns

Pattern 1: Research + Implement

Split research and implementation into parallel tracks:

Pane 1 (Research): "Research best practices for rate limiting in Node.js.
  Check current libraries, compare approaches, and write findings to
  /tmp/rate-limit-research.md"

Pane 2 (Implement): "Implement rate limiting middleware for our Express API.
  Start with a basic token bucket, we'll refine after research completes."

# After Pane 1 completes, merge findings into Pane 2's context

Pattern 2: Multi-File Feature

Parallelize work across independent files:

Pane 1: "Create the database schema and migrations for the billing feature"
Pane 2: "Build the billing API endpoints in src/api/billing/"
Pane 3: "Create the billing dashboard UI components"

# Merge all, then do integration in main pane

Pattern 3: Test + Fix Loop

Run tests in one pane, fix in another:

Pane 1 (Watcher): "Run the test suite in watch mode. When tests fail,
  summarize the failures."

Pane 2 (Fixer): "Fix failing tests based on the error output from pane 1"

Pattern 4: Cross-Harness

Use different AI tools for different tasks:

Pane 1 (OpenAI Codex): "Review the security of the auth module"
Pane 2 (Codex): "Refactor the utility functions for performance"
Pane 3 (OpenAI Codex): "Write E2E tests for the checkout flow"

Pattern 5: Code Review Pipeline

Parallel review perspectives:

Pane 1: "Review src/api/ for security vulnerabilities"
Pane 2: "Review src/api/ for performance issues"
Pane 3: "Review src/api/ for test coverage gaps"

# Merge all reviews into a single report

Best Practices

Independent tasks only. Don't parallelize tasks that depend on each other's output.
Clear boundaries. Each pane should work on distinct files or concerns.
Merge strategically. Review pane output before merging to avoid conflicts.
Use git worktrees. For file-conflict-prone work, use separate worktrees per pane.
Resource awareness. Each pane uses API tokens — keep total panes under 5-6.

Git Worktree Integration

For tasks that touch overlapping files:

# Create worktrees for isolation
git worktree add ../feature-auth feat/auth
git worktree add ../feature-billing feat/billing

# Run agents in separate worktrees
# Pane 1: cd ../feature-auth && codex
# Pane 2: cd ../feature-billing && codex

# Merge branches when done
git merge feat/auth
git merge feat/billing

Complementary Tools

Tool	What It Does	When to Use
dmux	tmux pane management for agents	Parallel agent sessions
Superset	Terminal IDE for 10+ parallel agents	Large-scale orchestration
OpenAI Codex Task tool	In-process subagent spawning	Programmatic parallelism within a session
Codex multi-agent	Built-in agent roles	Codex-specific parallel work

Troubleshooting

Pane not responding: Check if the agent session is waiting for input. Use m to read output.
Merge conflicts: Use git worktrees to isolate file changes per pane.
High token usage: Reduce number of parallel panes. Each pane is a full agent session.
tmux not found: Install with brew install tmux (macOS) or apt install tmux (Linux).

View source ↗

File metadata

name: dmux-workflows
description: Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across OpenAI Codex, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.

View original text

---
name: dmux-workflows
description: Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across OpenAI Codex, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.
---

# dmux Workflows

Orchestrate parallel AI agent sessions using dmux, a tmux pane manager for agent harnesses.

## When to Activate

- Running multiple agent sessions in parallel
- Coordinating work across OpenAI Codex, Codex, and other harnesses
- Complex tasks that benefit from divide-and-conquer parallelism
- User says "run in parallel", "split this work", "use dmux", or "multi-agent"

## What is dmux

dmux is a tmux-based orchestration tool that manages AI agent panes:
- Press `n` to create a new pane with a prompt
- Press `m` to merge pane output back to the main session
- Supports: OpenAI Codex, Codex, OpenCode, Cline, Gemini, Qwen

**Install:** `npm install -g dmux` or see [github.com/standardagents/dmux](https://github.com/standardagents/dmux)

## Quick Start

```bash
# Start dmux session
dmux

# Create agent panes (press 'n' in dmux, then type prompt)
# Pane 1: "Implement the auth middleware in src/auth/"
# Pane 2: "Write tests for the user service"
# Pane 3: "Update API documentation"

# Each pane runs its own agent session
# Press 'm' to merge results back
```

## Workflow Patterns

### Pattern 1: Research + Implement

Split research and implementation into parallel tracks:

```
Pane 1 (Research): "Research best practices for rate limiting in Node.js.
  Check current libraries, compare approaches, and write findings to
  /tmp/rate-limit-research.md"

Pane 2 (Implement): "Implement rate limiting middleware for our Express API.
  Start with a basic token bucket, we'll refine after research completes."

# After Pane 1 completes, merge findings into Pane 2's context
```

### Pattern 2: Multi-File Feature

Parallelize work across independent files:

```
Pane 1: "Create the database schema and migrations for the billing feature"
Pane 2: "Build the billing API endpoints in src/api/billing/"
Pane 3: "Create the billing dashboard UI components"

# Merge all, then do integration in main pane
```

### Pattern 3: Test + Fix Loop

Run tests in one pane, fix in another:

```
Pane 1 (Watcher): "Run the test suite in watch mode. When tests fail,
  summarize the failures."

Pane 2 (Fixer): "Fix failing tests based on the error output from pane 1"
```

### Pattern 4: Cross-Harness

Use different AI tools for different tasks:

```
Pane 1 (OpenAI Codex): "Review the security of the auth module"
Pane 2 (Codex): "Refactor the utility functions for performance"
Pane 3 (OpenAI Codex): "Write E2E tests for the checkout flow"
```

### Pattern 5: Code Review Pipeline

Parallel review perspectives:

```
Pane 1: "Review src/api/ for security vulnerabilities"
Pane 2: "Review src/api/ for performance issues"
Pane 3: "Review src/api/ for test coverage gaps"

# Merge all reviews into a single report
```

## Best Practices

1. **Independent tasks only.** Don't parallelize tasks that depend on each other's output.
2. **Clear boundaries.** Each pane should work on distinct files or concerns.
3. **Merge strategically.** Review pane output before merging to avoid conflicts.
4. **Use git worktrees.** For file-conflict-prone work, use separate worktrees per pane.
5. **Resource awareness.** Each pane uses API tokens — keep total panes under 5-6.

## Git Worktree Integration

For tasks that touch overlapping files:

```bash
# Create worktrees for isolation
git worktree add ../feature-auth feat/auth
git worktree add ../feature-billing feat/billing

# Run agents in separate worktrees
# Pane 1: cd ../feature-auth && codex
# Pane 2: cd ../feature-billing && codex

# Merge branches when done
git merge feat/auth
git merge feat/billing
```

## Complementary Tools

| Tool | What It Does | When to Use |
|------|-------------|-------------|
| **dmux** | tmux pane management for agents | Parallel agent sessions |
| **Superset** | Terminal IDE for 10+ parallel agents | Large-scale orchestration |
| **OpenAI Codex Task tool** | In-process subagent spawning | Programmatic parallelism within a session |
| **Codex multi-agent** | Built-in agent roles | Codex-specific parallel work |

## Troubleshooting

- **Pane not responding:** Check if the agent session is waiting for input. Use `m` to read output.
- **Merge conflicts:** Use git worktrees to isolate file changes per pane.
- **High token usage:** Reduce number of parallel panes. Each pane is a full agent session.
- **tmux not found:** Install with `brew install tmux` (macOS) or `apt install tmux` (Linux).

Review the source

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 89 GitHub stars
Stars/forks activity: 89 stars, 2 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

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Source & usage notes

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Source repository: mturac/everything-openai-codex
License: MIT
Version: 1.0.0
Last GitHub push: Aug 24, 2026
Registry updated: Sep 7, 2026
Instruction path: .agents/skills/dmux-workflows/SKILL.md @ b5057da5f42e

Version reported in registry metadata; check source releases before relying on it.

Quality

66/100

Promising

Trust

60/100

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More details

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