dmux-workflows/SKILL.md
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.
npx skillsauth add lidge-jun/cli-jaw-skills dmux-workflowsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
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 -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
| 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 |
tmux capture-pane -pt <session>:0.<pane-index>.brew install tmux (macOS) or apt install tmux (Linux).development
Goal execution guidelines with PABCD integration, verification tiers, documentation workflow, and AI-driven planning
tools
A CLI tool for making authenticated requests to the X (Twitter) API. Use this skill when you need to post tweets, reply, quote, search, read posts, manage followers, send DMs, upload media, or interact with any X API v2 endpoint.
development
Use this skill any time a spreadsheet file is the primary input or output (.xlsx, .xlsm, .csv, .tsv). This includes: creating, reading, editing, analyzing, or formatting spreadsheets; cleaning messy tabular data; converting between formats; and data visualization with charts. Also use for pandas-based data analysis when the deliverable is a spreadsheet. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration.
tools
Use this skill when the user wants to build a financial model, 3-statement model, DCF valuation, cap table, scenario analysis, or financial projections in Excel. Trigger on: 'financial model', '3-statement model', 'DCF', 'cap table', 'pro forma', 'projections', 'sensitivity analysis', 'waterfall', 'debt schedule', 'break-even', 'discounted cash flow', 'capitalization table', 'fundraising model', 'WACC calculation', 'scenario analysis model'. Input is a text prompt with assumptions. Output is a single .xlsx file with formula-driven, interconnected statement sheets.