general-purpose-orchestrator

To orchestrate a multi-agent AI workflow pipeline, you use a deterministic run algorithm that discovers pipeline items, dispatches stages to specialized subagents, and consolidates results into a structured final report for audit.

The best way to coordinate subagents for automated task dispatch is to use an orchestration skill that assigns specific pipeline stages to each agent, tracks execution end-to-end, and classifies outcomes into an auditable execution trace.

Yes, pipeline orchestration tracks multiple specialized AI agents simultaneously by applying a deterministic dispatch mechanism that routes tasks across the workflow and generates a final structured report path for review.

A deterministic run algorithm handles pipeline item discovery by scanning the provided inputs, identifying sequential stages, and strictly routing each task to the appropriate subagent to ensure a cohesive and auditable execution trace.

Yes, you need to provide /run inputs to trigger automated pipeline orchestration, which the system uses to discover items, dispatch stages across subagents, and output a final report path for review.

You should not use an automated orchestrator for your AI agent workflow if your tasks do not require multi-stage dispatch, specialized subagent coordination, or strict end-to-end reporting and auditability.