agent-teams

Multi-agent coordination is achieved by defining a lead agent to distribute subtasks, manage a shared task list, and synthesize findings from teammate agents researching different aspects simultaneously. This enables efficient parallel research, review, or problem-solving for complex tasks.

Structuring competing hypotheses involves configuring teammate agents to explore different implementation approaches independently, then using a lead agent to synthesize the findings. This multi-agent coordination pattern allows simultaneous evaluation of competing solutions for complex problem-solving.

Setting up bidirectional messaging requires defining roles for a lead agent and teammates, then establishing a shared task list. The lead agent manages task distribution and monitors progress, enabling dynamic communication and continuous collaboration between agents during complex workflows.

Yes, multi-agent coordination supports parallel code review by assigning specific agents to analyze security and performance independently. A lead agent manages the task distribution, monitors progress, and synthesizes the review findings for comprehensive code analysis.

A multi-agent team is ideal for complex tasks requiring parallel research, review, or competing approaches that would be inefficient for a single agent. It optimizes collaborative workflows by enabling simultaneous task execution, dynamic communication, and structured coordination.

No specific dependencies are required to manage parallel processing with agent-teams. The skill facilitates multi-agent coordination internally through shared task lists and bidirectional messaging, structuring collaborative workflows without external library constraints.