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tiandiyiqi
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编排

Orchestrate multi-agent workflows with dependency graphs and real-time progress via TodoWrite.

Updated Jan 26, 2026
Search Tags:#automation#workflow#task management#dependency management#multi-agent#orchestration
One-click install
npx skills add https://github.com/tiandiyiqi/ai-skills --skill -tiandiyiqi
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: 编排
Source: https://github.com/tiandiyiqi/ai-skills/tree/main/%E5%B7%A5%E4%BD%9C%E6%B5%81%E4%B8%8E%E4%BB%A3%E7%90%86/%E7%BC%96%E6%8E%92
Command: npx skills add https://github.com/tiandiyiqi/ai-skills --skill -tiandiyiqi

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates the coordination and execution of complex tasks that require multiple agents working in parallel or sequence, managing dependencies and providing real-time progress visibility.

Core Features & Use Cases

  • Multi-Agent Coordination: Orchestrates multiple AI agents to tackle large, decomposed tasks.
  • Dependency Management: Uses cc-mirror tasks to define and track task dependencies, ensuring work is done in the correct order.
  • Real-time Visibility: Utilizes TodoWrite to provide users with live progress updates.
  • Use Case: When a user requests a complex feature implementation, this Skill breaks it down into manageable sub-tasks, assigns them to specialized agents, tracks their progress, and synthesizes the results into a cohesive deliverable.

Quick Start

Use the 编排 skill to break down the task 'Implement user authentication' into smaller, manageable steps.

Frequently Asked Questions about 编排

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I orchestrate complex multi-agent workflows for task automation?▼

Multi-agent workflow orchestration decomposes complex tasks into a dependency graph managed by `cc-mirror tasks`, handling parallel execution, dependency tracking, and agent spawning for deterministic and coordinated task completion.

How does dependency management work for parallel task execution?▼

Dependency management for parallel execution uses `cc-mirror tasks` to define and track task dependencies, ensuring work is done in the correct order while providing real-time session visibility via `TodoWrite`.

What is the best way to track real-time progress for automated multi-agent tasks?▼

Real-time progress tracking for automated multi-agent tasks is handled by `TodoWrite`, which provides live session visibility as agents execute decomposed sub-tasks in parallel or sequence.

Can I break down a large feature implementation into manageable sub-tasks automatically?▼

Breaking down a large feature implementation into manageable sub-tasks is supported by decomposing the request into a dependency graph, assigning sub-tasks to specialized agents, and synthesizing results into a cohesive deliverable.

Do I need any external dependencies to coordinate multiple AI agents?▼

No external dependencies are required to coordinate multiple AI agents; the skill relies on its internal `cc-mirror tasks` dependency graph and `TodoWrite` for session visibility to manage orchestration natively.

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