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orchestration

Coordinate multi-agent teams and subagents under RAM and security constraints.

Updated Feb 10, 2026
Search Tags:#agent#orchestration#resource management#ai workflow#subagent#team coordination
One-click install
npx skills add https://github.com/eysenfalk/git-review --skill orchestration-eysenfalk
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: orchestration
Source: https://github.com/eysenfalk/git-review/tree/main/.claude/skills/orchestration
Command: npx skills add https://github.com/eysenfalk/git-review --skill orchestration-eysenfalk

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a framework for deciding when to use teams versus subagents, managing resource constraints, and understanding enforcement hooks, enabling efficient coordination of multi-agent work.

Core Features & Use Cases

  • Agent Coordination: Decide between teams for peer communication or subagents for parallel tasks.
  • Resource Management: Adhere to RAM limits by preferring subagents for parallelism.
  • Enforcement Awareness: Understand and respect security hooks that might block actions.
  • Use Case: When initiating a complex project requiring multiple AI agents, use this Skill to determine the optimal setup for collaboration and resource allocation, ensuring smooth execution and preventing system overload.

Quick Start

Use the orchestration skill to spawn a team of three coders to work on the new feature.

Frequently Asked Questions about orchestration

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

FAQPage Schema
How do I coordinate multiple AI agents for complex task decomposition?▼

To coordinate multiple AI agents, this skill provides a framework for deciding between teams for peer communication or subagents for parallel tasks, ensuring efficient work execution.

When should I use AI agent teams versus subagents for parallel tasks?▼

You should use teams when you need peer communication between agents, and prefer subagents for parallel tasks to adhere to RAM limits and manage resource constraints effectively.

How do I manage RAM limits when spawning parallel AI agents?▼

You can manage RAM limits by preferring subagents for parallelism, which enforces resource constraints and prevents system overload during complex multi-agent workflows.

What are enforcement hooks in multi-agent AI workflows?▼

Enforcement hooks in multi-agent workflows are security protocols that might block actions, requiring agents to understand and respect them to ensure safe execution during task coordination.

Can I spawn a team of AI coders to work on a new feature simultaneously?▼

Yes, you can spawn a team of three coders to work on a new feature, using the orchestration framework to determine optimal setup for collaboration and resource allocation.

What are the limitations of using teams instead of subagents for AI agent coordination?▼

Using teams instead of subagents may cause system overload because teams do not enforce RAM limits as strictly, making subagents preferable for parallel tasks to maintain resource constraints.

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