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docs: add native Japanese translation of ECC documentation (ja-JP)
Translate everything-claude-code repository to Japanese including: - 17 root documentation files - 60 agent documentation files - 80 command documentation files - 99 rule files across 18 language directories (common, angular, arkts, cpp, csharp, dart, fsharp, golang, java, kotlin, perl, php, python, ruby, rust, swift, typescript, web) - 199 skill documentation files Total: 455 files translated to Japanese with: - Consistent terminology glossary applied throughout - YAML field names preserved in English (name, description, etc.) - Code blocks and examples untouched (comments translated) - Markdown structure and relative links preserved - Professional translation maintaining technical accuracy This translation expands ECC accessibility to Japanese-speaking developers and teams. Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
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docs/ja-JP/skills/dmux-workflows/SKILL.md
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docs/ja-JP/skills/dmux-workflows/SKILL.md
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---
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name: dmux-workflows
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description: 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。
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origin: ECC
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---
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# dmux ワークフロー
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複数のエージェントとタスク集約処理の調整。
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## 使用時期
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- 複数のタスクを並行して実行
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- 大規模なワークフローを調整
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- エージェント間でタスクを分配
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- エラーハンドリングとリトライ
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- 結果のマージと統合
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## アーキテクチャ
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```
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Input Task
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↓
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[Dispatcher]
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↓
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├─ Worker 1 → Task A
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├─ Worker 2 → Task B
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├─ Worker 3 → Task C
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↓
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[Result Merger]
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↓
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Unified Output
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```
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## 実装
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### 1. タスク定義
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```python
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tasks = [
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Task(id=1, work="process data A"),
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Task(id=2, work="process data B"),
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Task(id=3, work="process data C"),
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]
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```
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### 2. Dispatch
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```python
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dispatcher.run_parallel(tasks, workers=3)
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```
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### 3. Results
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```python
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results = dispatcher.get_results()
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merged = merge_results(results)
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```
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## ベストプラクティス
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- [ ] タスク粒度を適切に設定
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- [ ] エラーハンドリング
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- [ ] ロギング
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- [ ] モニタリング
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- [ ] タイムアウト管理
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詳細については、ドキュメントを参照してください。
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