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sumeetonline90
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dmux-workflows

Coordinates parallel AI agent sessions across multiple tmux panes and harnesses.

Updated Jun 25, 2026
Search Tags:#ai agents#multi-agent#tmux#code collaboration#development orchestration#dmux#parallel workflows
One-click install
npx skills add https://github.com/sumeetonline90/fitup_all --skill dmux-workflows-sumeetonline90
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dmux-workflows
Source: https://github.com/sumeetonline90/fitup_all/tree/main/.cursor/.agents/skills/dmux-workflows
Command: npx skills add https://github.com/sumeetonline90/fitup_all --skill dmux-workflows-sumeetonline90

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Manually coordinating multiple parallel AI agent sessions across different harnesses like Claude Code, Codex, and OpenCode is tedious, error-prone, and wastes time switching between terminals and merging disjointed work.

Core Features & Use Cases

  • Parallel Agent Management: Use dmux to create and manage multiple tmux panes, each running an independent AI agent session for supported harnesses including Claude Code, Codex, OpenCode, Cline, Gemini, and Qwen.
  • Built-in Workflow Patterns: Leverage pre-defined templates for common multi-agent workflows including research + implementation, multi-file feature development, test-fix loops, cross-harness task assignment, and parallel code review.
  • Use Case: For a full-stack feature build, assign one agent to handle database schema and migrations, a second to build API endpoints, and a third to create UI components, then merge all results into a single cohesive implementation.

Quick Start

Use the dmux-workflows skill to split a complex development task into parallel agent tracks for independent workstreams, then merge all outputs into a unified final result.

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 multi-file feature development?▼

You can run parallel AI agent sessions by using tmux pane management to coordinate independent workstreams across multiple harnesses, then merge the outputs into a unified implementation.

What is the best way to coordinate multiple AI agents across different harnesses like Claude Code and Codex?▼

Coordinating multiple AI agents across harnesses like Claude Code and Codex is handled by using tmux pane management to create independent agent sessions and built-in workflow patterns to assign cross-tool tasks.

Can I use tmux to manage cross-harness AI agent workflows?▼

Yes, tmux can manage cross-harness AI agent workflows by creating separate panes for each supported agent session, enabling divide-and-conquer parallelism across tools like Gemini and Qwen.

How do I prevent git conflicts when running multiple AI agents in parallel?▼

To prevent git conflicts during parallel AI agent execution, you can utilize git worktree integration to isolate workstreams and apply built-in merge controls to consolidate agent outputs cleanly.

Does parallel workflow orchestration support test-fix loops and parallel code review?▼

Parallel workflow orchestration supports test-fix loops and parallel code review through built-in workflow templates designed for common multi-agent development patterns.

Why use built-in workflow patterns for multi-agent development orchestration?▼

Built-in workflow patterns for multi-agent orchestration solve the tedious, error-prone manual coordination of switching between terminals and merging disjointed work from independent AI agents.

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