parallel-agents

Multi-agent orchestration coordinates multiple specialized agents to perform parallel analysis and synthesis, passing context between agents to maintain a single, coherent synthesized report. It applies predefined sequences to map, analyze, and synthesize results.

Multi-agent orchestration is needed for complex tasks requiring multi-perspective reviews, security audits, architecture analyses, and cross-domain evaluations. It reduces turnaround time and increases thoroughness by applying specialized agents in parallel.

To orchestrate a multi-agent review, use predefined orchestration patterns that map, analyze, and synthesize results. The skill passes context and findings between agents to produce a unified summary and actionable recommendations.

Yes, multi-agent orchestration supports cross-domain evaluations and security audits by coordinating specialized agents. It applies context passing to share findings between agents, ensuring a single synthesized report with actionable recommendations.

The best way to synthesize findings from parallel AI agents is using a predefined orchestration sequence that passes context between agents. This approach produces a unified summary and actionable recommendations in a single synthesized report.

No, multi-agent orchestration does not require external dependencies to function. The skill operates independently using predefined sequences of agents to map, analyze, and synthesize results into a unified report.