What is a prerequisite for using this skill?

You should first run a planning skill to generate an 'execution-plan.md' file, which serves as the blueprint for the Orchestrator to assign tasks.

Can it handle file conflicts between agents?

Yes, the Orchestrator monitors file reservations and can send messages to specific agents to request file releases or resolve overlapping work areas.

What is the Orchestrator skill used for?

It is used to manage and supervise multiple autonomous worker agents working on different parts of a large project simultaneously, ensuring they stay coordinated.

Does it support parallel execution?

Yes, it uses the Task tool to spawn multiple worker sub-agents that run in parallel, significantly speeding up the completion of complex epics.

How does the Orchestrator communicate with worker agents?

It uses the Agent Mail MCP to register identities, send messages, and monitor progress threads, allowing agents to exchange context and report completions.

Orchestrator Agent Coordinator

Name: Orchestrator Agent Coordinator
Author: draphonix

bydraphonix

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协作工具

Coordinates and monitors multiple autonomous worker agents to execute complex, parallelized coding tasks.

关于

The Orchestrator skill enables Claude to act as a project manager, supervising a fleet of parallel worker agents to tackle large-scale software features or 'epics.' It systematically reads execution plans, spawns specialized sub-agents via the Task tool, and manages inter-agent communication using the Agent Mail protocol. By handling cross-track blockers and file conflict resolutions autonomously, this skill allows for high-velocity development across multiple modules while maintaining a centralized source of truth for progress and learnings.

主要功能

Automated progress monitoring and bead status tracking
49 GitHub stars
Parallel worker agent spawning and lifecycle management
Centralized communication via Agent Mail MCP integration
Comprehensive epic completion reporting and documentation
Cross-track dependency and blocker resolution

使用场景

Managing large-scale feature developments with multiple independent work tracks
Parallelizing repository-wide updates such as documentation or dependency migrations
Coordinating complex refactors across different packages or microservices

关于

主要功能

Automated progress monitoring and bead status tracking
49 GitHub stars
Parallel worker agent spawning and lifecycle management
Centralized communication via Agent Mail MCP integration
Comprehensive epic completion reporting and documentation
Cross-track dependency and blocker resolution

使用场景

Managing large-scale feature developments with multiple independent work tracks
Parallelizing repository-wide updates such as documentation or dependency migrations
Coordinating complex refactors across different packages or microservices