Dmux Workflows

by affaan-mef648e01899ba3e8dc6371642deaaf64b4477775No license275K starsListed Oct 9, 2026Updated Oct 9, 2026Repository updated 4 days ago

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。

Instructions onlyAI & Agents

AI-generated overview

Coordinates multiple AI agents and task aggregation workflows, distributing work across workers and merging results.

What it does: This skill provides guidance for orchestrating parallel AI agent work: defining tasks, dispatching them to multiple workers, handling errors and retries, and merging results into a unified output. It describes a dispatcher/worker/result-merger architecture with illustrative code snippets and a best-practices checklist covering task granularity, error handling, logging, monitoring, and timeouts. It is instructions only and produces no files or scripts.
When to use it: Use it when running several tasks in parallel, coordinating large workflows, distributing tasks among agents, or needing error handling, retries, and result merging. It suits orchestration planning rather than single-task execution.
Requirements: No scripts or assets ship with the skill; it is instructions only. Following it assumes an environment capable of running multiple AI agents or workers, but no specific tools, packages, credentials, or network access are stated.

dmux ワークフロー

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

Input Task    ↓[Dispatcher]    ↓├─ Worker 1 → Task A├─ Worker 2 → Task B├─ Worker 3 → Task C    ↓[Result Merger]    ↓Unified Output

python

tasks = [    Task(id=1, work="process data A"),    Task(id=2, work="process data B"),    Task(id=3, work="process data C"),]

tasks = [    Task(id=1, work="process data A"),    Task(id=2, work="process data B"),    Task(id=3, work="process data C"),]

詳細については、ドキュメントを参照してください。

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.