Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/JunMystery/Agent-Guidance-Pythonnpx agentmods add skills/junmystery/agent-guidance-python/dmux-workflowsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/junmystery/agent-guidance-python/dmux-workflows)<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/dmux-workflows"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/dmux-workflows/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/junmystery/agent-guidance-python/dmux-workflows"><img src="https://agentmods.dev/badge/skills/junmystery/agent-guidance-python/dmux-workflows.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.01567 |
| Opus 5.5 | $0.00022 | $0.00627 |
| Sonnet 5.5 | $0.00011 | $0.00313 |
| Haiku 4.5 | $0.00006 | $0.00157 |
Grade A, and why
dmux-workflows scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to dmux-workflows — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
nto create a new pane with a prompt - Press
mto 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:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 192 lines · 56 tokens per session scan A d82ed05f4713
dmux-workflows is a skill published in the GitHub repository JunMystery/Agent-Guidance-Python (2 stars, last pushed 3mo ago), licensed MIT. It adds 56 tokens to every session and 1,567 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to dmux-workflows, differing in 0 lines, and is treated as a copy.
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