orchestrator

Coordinate multiple sub-agents across a four-phase workflow to execute complex tasks.

Updated Nov 23, 2025

Search Tags:#workflow #planning #orchestrator #parallel-execution #sub-agent #task-automation

Ready to run

npx skills add https://github.com/vinzenz/jules-agentic-software-builder-for-claude --skill orchestrator-vinzenz

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: orchestrator
Source: https://github.com/vinzenz/jules-agentic-software-builder-for-claude/tree/main/.claude/skills/orchestrator
Command: npx skills add https://github.com/vinzenz/jules-agentic-software-builder-for-claude --skill orchestrator-vinzenz

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a structured orchestrator to manage complex tasks by coordinating multiple sub-agents across a four-phase workflow: planning, delegation, parallel execution, and aggregation.

Core Features & Use Cases

Planning: Analyze the objective and decompose it into discrete work items.
Delegation & Parallelization: Assign items to specialized sub-agents and execute independent items in parallel.
Aggregation: Collect, reconcile, and summarize outputs from all sub-agents to form a cohesive result.
Use Case: Orchestrate a data-processing pipeline that collects data from several sources, processes steps in parallel, and merges results into a final report.

Quick Start

Provide a complex objective and let the orchestrator plan, assign sub-tasks, run them in parallel where possible, and return a unified outcome.

Frequently Asked Questions about orchestrator

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

FAQPage Schema

How do I coordinate multiple AI sub-agents for parallel task execution?▼

To coordinate multiple AI sub-agents for parallel task execution, you provide a complex objective to the orchestrator, which decomposes it into discrete work items, delegates them to specialized sub-agents, and executes independent items simultaneously before aggregating the results into a unified outcome.

What is a multi-phase workflow for AI task automation?▼

A multi-phase workflow for AI task automation is a structured process that breaks down complex objectives into four stages: planning, delegation, parallel execution monitoring, and result aggregation across modular sub-agents to produce a cohesive final output.

How do I aggregate results from parallel AI agents into a single report?▼

You aggregate results from parallel AI agents by using an orchestration layer that collects, reconciles, and summarizes the outputs from all delegated sub-agents after their parallel execution completes, forming a cohesive final report.

Can I use this orchestrator skill to run a data-processing pipeline with parallel steps?▼

Yes, you can use this orchestrator skill to run a data-processing pipeline. It supports scenarios where the orchestrator collects data from several sources, processes steps in parallel via sub-agents, and merges the results into a final report.

When should I use a multi-agent orchestrator instead of a single AI assistant?▼

You should use a multi-agent orchestrator instead of a single AI assistant when your objective requires planning, delegation, and parallel execution across modular agents, especially for complex tasks that exceed the capacity of a single workflow step.

Do I need any external dependencies to run the multi-agent orchestrator workflow?▼

No, you do not need any external dependencies to run the multi-agent orchestrator workflow. The skill operates independently without requiring additional components or external libraries to execute its planning, delegation, and aggregation phases.