Best fit
- 複数のAIエージェントとタスク集約ワークフローを調整します。複数のワーカーで作業を分配し、エラーを処理し、結果をマージ。
affaan-m/ECC
複数のAIエージェントとタスク集約ワークフローを調整します。複数のワーカーで作業を分配し、エラーを処理し、結果をマージ。
npx skills add https://github.com/affaan-m/ECC --skill "docs/ja-JP/skills/dmux-workflows"Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Reorganized from the pinned upstream SKILL.md
According to the pinned SKILL.md from affaan-m/ECC: 複数のAIエージェントとタスク集約ワークフローを調整します。複数のワーカーで作業を分配し、エラーを処理し、結果をマージ。
npx skills add https://github.com/affaan-m/ECC --skill "docs/ja-JP/skills/dmux-workflows"Best fit
Bring this context
Expected outputs
Key source sections
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
複数のタスクを並行して実行
Review the “アーキテクチャ” section in the pinned source before continuing.
Review the “実装” section in the pinned source before continuing.
Review the “1. タスク定義” section in the pinned source before continuing.
Review the “2. Dispatch” section in the pinned source before continuing.
SkillSignal prompt templates
These prompts were written by SkillSignal from the source structure; they are not upstream text.
Task-start prompt
Confirm source fit, inputs, and outputs before acting.
Use dmux-workflows to help me with: [specific task]. Context: [files, data, or background]. Constraints: [environment, scope, and prohibited actions]. Before acting, check the pinned SKILL.md and explain which sections apply, what inputs are still missing, and what you will deliver.
Source-guided execution
Make the Agent explicitly follow the key extracted sections.
Apply the pinned dmux-workflows source to [task]. Pay particular attention to these source sections: “使用時期”, “アーキテクチャ”, “実装”, “1. タスク定義”, “2. Dispatch”. Preserve the important decision at each step. Mark facts not covered by the source as “needs confirmation” instead of inventing them. Then verify the result against my acceptance criteria: [criteria].
Result-review prompt
Check omissions, permissions, and source drift before delivery.
Review the current dmux-workflows result: (1) does it satisfy the original task; (2) were any applicable steps or limits in the pinned SKILL.md missed; (3) did it perform any unauthorized file, command, network, or data action; and (4) which conclusions remain unverified? List issues first, then fix only what the source or user authorization supports.
Output checklist
The task matches the purpose documented in the SKILL.md.
The source section “使用時期” has been checked.
The source section “アーキテクチャ” has been checked.
The source section “実装” has been checked.
The source section “1. タスク定義” has been checked.
Inputs, constraints, and acceptance criteria are explicit.
Unverified facts, compatibility, and outcome claims are clearly marked.
Any file, command, network, or data action has been reviewed.
Choose a different workflow
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.
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detailMulti-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.
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detail使用dmux(AI代理的tmux窗格管理器)进行多代理编排。跨Claude Code、Codex、OpenCode及其他工具的并行代理工作流模式。适用于并行运行多个代理会话或协调多代理开发工作流时。
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detailFAQ
複数のAIエージェントとタスク集約ワークフローを調整します。複数のワーカーで作業を分配し、エラーを処理し、結果をマージ。
The catalog detected this source-specific install command: npx skills add https://github.com/affaan-m/ECC --skill "docs/ja-JP/skills/dmux-workflows". Inspect the command and pinned source before running it.
No dedicated Agent platform is declared in the pinned source record.
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Compare before choosing
These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.
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.
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.
使用dmux(AI代理的tmux窗格管理器)进行多代理编排。跨Claude Code、Codex、OpenCode及其他工具的并行代理工作流模式。适用于并行运行多个代理会话或协调多代理开发工作流时。
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program
When the user wants to reduce churn, build cancellation flows, set up save offers, recover failed payments, or implement retention strategies. Also use when the user mentions 'churn,' 'cancel flow,' 'offboarding,' 'save offer,' 'dunning,' 'failed payment recovery,' 'win-back,' 'retention,' 'exit survey,' 'pause subscription,' 'involuntary churn,' 'people keep canceling,' 'churn rate is too high,' 'how do I keep users,' or 'customers are leaving.' Use this whenever someone is losing subscribers o
複数のエージェントとタスク集約処理の調整。
Input Task
↓
[Dispatcher]
↓
├─ Worker 1 → Task A
├─ Worker 2 → Task B
├─ Worker 3 → Task C
↓
[Result Merger]
↓
Unified Output
tasks = [
Task(id=1, work="process data A"),
Task(id=2, work="process data B"),
Task(id=3, work="process data C"),
]
dispatcher.run_parallel(tasks, workers=3)
results = dispatcher.get_results()
merged = merge_results(results)
詳細については、ドキュメントを参照してください。