multi-model-orchestrator

Multi-agent orchestration coordinates complex tasks across multiple AI agents like Claude, Opus, and Haiku using a centralized handoff document. This single source of truth manages goal decomposition, parallel execution, and end-to-end traceability across cross-agent workflows.

Execution tracking in a multi-agent workflow uses a structured handoff schema to capture decisions, blockers, and learnings. It assigns subtasks with explicit dependencies and synthesizes outcomes into actionable next steps using evidence-based feedback fusion.

Yes, a single handoff document supports parallel task decomposition across Claude Code and Codex. It serves as the centralized source of truth, allowing you to maximize throughput by executing subtasks in parallel while maintaining end-to-end traceability.

To start a multi-agent project, copy the handoff-template.yaml file to your local `.claude/handoffs/` directory. Fill in your project goal and subtasks, then prompt your AI agent to decompose and execute the structured workflow.

A centralized agent handoff document requires a structured schema containing metadata, the primary goal, subtasks, execution rounds, and a final synthesis. This format ensures structured handoffs and end-to-end traceability across cross-agent workflows.

A centralized handoff document is not suited for single-agent tasks or workflows lacking complex cross-agent dependencies. It is designed specifically for parallel decomposition, execution tracking, and feedback fusion across multiple AI agents.