
Dmux Workflows
Run parallel Claude Code, Codex, OpenCode, and other agent panes with dmux tmux orchestration and merge outputs back to the main session.
Overview
dmux Workflows is a journey-wide agent skill that coordinates parallel AI agent sessions in tmux via dmux—usable whenever a solo builder needs to split work across harnesses before merging results.
Install
npx skills add https://github.com/affaan-m/everything-claude-code --skill dmux-workflowsWhat is this skill?
- tmux-based dmux: press `n` for new agent pane prompts, `m` to merge pane output to the main session
- Supports Claude Code, Codex, OpenCode, Cline, Gemini, and Qwen harnesses
- Documented patterns include Research + Implement parallel split and test/doc fan-out
- Activate when user says run in parallel, split this work, use dmux, or multi-agent
- Install dmux from standardagents repository after reviewing the package
- Six named harness families: Claude Code, Codex, OpenCode, Cline, Gemini, Qwen
- Three core dmux keys documented: n (new pane), m (merge)
Adoption & trust: 4k installs on skills.sh; 210k GitHub stars; 2/3 security scanners passed (skills.sh audits).
What problem does it solve?
One agent session cannot efficiently cover implement, test, and document at once, and you lack a repeatable tmux pattern to run harnesses in parallel.
Who is it for?
Advanced solo builders comfortable with tmux who routinely use Claude Code or Codex and want divide-and-conquer on multi-file tasks.
Skip if: Beginners without tmux, or trivial one-file edits where orchestration overhead exceeds any time saved.
When should I use this skill?
Running multiple agent sessions in parallel, coordinating multi-harness development, or when the user says run in parallel, split this work, use dmux, or multi-agent.
What do I get? / Deliverables
You run dmux with scoped pane prompts, let each harness execute in parallel, then merge consolidated output back into the main session with `m`.
- Parallel agent pane outputs merged into the main dmux session
- Documented pattern choice (e.g. research + implement) for the task
Recommended Skills
Journey fit
Useful at every journey phase - explore requirements and options before committing to a direction.
Where it fits
Pane one implements auth middleware while pane two writes user-service tests before merge.
A dedicated pane updates API documentation while another pane lands the endpoint code.
Parallel panes run overlapping test suites on branches before you merge with `m`.
One pane reproduces a production error while another patches a hotfix path.
Research pane explores library options while implement pane spikes the chosen approach.
How it compares
Use for tmux multi-pane agent orchestration—not a single-thread chat skill or a CI matrix runner.
Common Questions / FAQ
Who is dmux-workflows for?
Developers already using Claude Code, Codex, or similar harnesses who want parallel panes and a documented merge workflow via dmux.
When should I use dmux-workflows?
Use during Build for parallel implementation and tests; during Ship when splitting review fixes and test runs; during Operate when debugging unrelated subsystems in parallel; whenever the user asks to run in parallel or use dmux.
Is dmux-workflows safe to install?
The skill points you to install dmux from its upstream repository—review the Security Audits panel on this page and audit that package before installing.
SKILL.md
READMESKILL.md - Dmux 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 Claude Code, 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: Claude Code, Codex, OpenCode, Cline, Gemini, Qwen **Install:** Install dmux from its repository after reviewing the package. 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 (Claude Code): "Review the security of the auth module" Pane 2 (Codex): "Refactor the utility functions for performance" Pane 3 (Claude Code): "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 -b feat/auth ../feature-auth HEAD git worktree add -b feat/billing ../feature-billing HEAD # Run agents in separate worktrees # Pane 1: cd ../feature-auth && claude # Pane 2: cd ../feature-billing && claude # Merge branches when done git merge feat/auth git merge feat/billing ``` ## Complementary Tools | Tool | What It Does | When t