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dmux-workflows

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

dmux-workflows 是什么?

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

兼容平台Claude CodeCodex CLI~CursorGemini CLIOpenCode
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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 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

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 (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:

# 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

ToolWhat It DoesWhen to Use
dmuxtmux pane management for agentsParallel agent sessions
SupersetTerminal IDE for 10+ parallel agentsLarge-scale orchestration
Claude Code Task toolIn-process subagent spawningProgrammatic parallelism within a session
Codex multi-agentBuilt-in agent rolesCodex-specific parallel work

ECC Helper

ECC now includes a helper for external tmux-pane orchestration with separate git worktrees:

node scripts/orchestrate-worktrees.js plan.json --execute

Example plan.json:

{
  "sessionName": "skill-audit",
  "baseRef": "HEAD",
  "launcherCommand": "codex exec --cwd {worktree_path} --task-file {task_file}",
  "workers": [
    { "name": "docs-a", "task": "Fix skills 1-4 and write handoff notes." },
    { "name": "docs-b", "task": "Fix skills 5-8 and write handoff notes." }
  ]
}

The helper:

  • Creates one branch-backed git worktree per worker
  • Optionally overlays selected seedPaths from the main checkout into each worker worktree
  • Writes per-worker task.md, handoff.md, and status.md files under .orchestration/<session>/
  • Starts a tmux session with one pane per worker
  • Launches each worker command in its own pane
  • Leaves the main pane free for the orchestrator

Use seedPaths when workers need access to dirty or untracked local files that are not yet part of HEAD, such as local orchestration scripts, draft plans, or docs:

{
  "sessionName": "workflow-e2e",
  "seedPaths": [
    "scripts/orchestrate-worktrees.js",
    "scripts/lib/tmux-worktree-orchestrator.js",
    ".claude/plan/workflow-e2e-test.json"
  ],
  "launcherCommand": "bash {repo_root}/scripts/orchestrate-codex-worker.sh {task_file} {handoff_file} {status_file}",
  "workers": [
    { "name": "seed-check", "task": "Verify seeded files are present before starting work." }
  ]
}

Troubleshooting

  • Pane not responding: Switch to the pane directly or inspect it with tmux capture-pane -pt <session>:0.<pane-index>.
  • 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).

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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