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.
From eccnpx claudepluginhub tatematsu-k/ai-development-skills --plugin eccThis skill uses the workspace's default tool permissions.
Searches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.
Searches prompts.chat for AI prompt templates by keyword or category, retrieves by ID with variable handling, and improves prompts via AI. Use for discovering or enhancing prompts.
Compares coding agents like Claude Code and Aider on custom YAML-defined codebase tasks using git worktrees, measuring pass rate, cost, time, and consistency.
Orchestrate parallel AI agent sessions using dmux, a tmux pane manager for agent harnesses.
dmux is a tmux-based orchestration tool that manages AI agent panes:
n to create a new pane with a promptm to merge pane output back to the main sessionInstall: npm install -g dmux or see github.com/standardagents/dmux
# 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
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
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
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"
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"
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
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 && claude
# Pane 2: cd ../feature-billing && claude
# Merge branches when done
git merge feat/auth
git merge feat/billing
| 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 |
| Claude Code Task tool | In-process subagent spawning | Programmatic parallelism within a session |
| Codex multi-agent | Built-in agent roles | Codex-specific parallel work |
m to read output.brew install tmux (macOS) or apt install tmux (Linux).