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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.

DeepseekModel 官方收录技能 质量 优秀 · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=affaan-m-ecc-agents-skills-dmux-workflows-skill-md&format=skill
下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name dmux-workflows description 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 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: npm install -g dmux or 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 Independent tasks only. Don't parallelize tasks that depend on each other's output. Clear boundaries. Each pane should work on distinct files or concerns. Merge strategically. Review pane output before merging to avoid conflicts. Use git worktrees. For file-conflict-prone work, use separate worktrees per pane. 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 ../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 Complementary Tools 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 Troubleshooting Pane not responding: Check if the agent session is waiting for input. Use m to read output. 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).
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下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
source_url来源链接(本页地址)
exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

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