Orchestrate parallel AI agent sessions using dmux, a tmux pane manager for agent harnesses.
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AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondmux-workflowsExecute the skills CLI command in your project's root directory to begin installation:
Fetches dmux-workflows from affaan-m/everything-claude-code and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate dmux-workflows. Access via /dmux-workflows in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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: Install dmux from its repository after reviewing the package. 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 |
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:
seedPaths from the main checkout into each worker worktreetask.md, handoff.md, and status.md files under .orchestration/<session>/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." }
]
}
tmux capture-pane -pt <session>:0.<pane-index>.brew install tmux (macOS) or apt install tmux (Linux).Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Useful defaults in dmux-workflows — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
dmux-workflows fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
dmux-workflows has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend dmux-workflows for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
dmux-workflows fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added dmux-workflows from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for dmux-workflows matched our evaluation — installs cleanly and behaves as described in the markdown.
dmux-workflows reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in dmux-workflows — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for dmux-workflows matched our evaluation — installs cleanly and behaves as described in the markdown.
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