do-agent

Multi-stage workflow automation is achieved by orchestrating up to ten parallel sub-agents per stage with explicit input and output files. The system generates temporary workspaces, executes all agents automatically, and tracks progress without requiring manual intervention.

Multi-agent orchestration is a coordinated hierarchy where sub-agents execute tasks in parallel, followed by iterative review and revision phases. It enforces context protection and file-based communication to refine results systematically across complex stages.

Fully automated parallel processing runs without human intervention by enforcing context protection and file-based communication across all agents. The system handles workspace generation, execution, and progress tracking independently once the workflow is defined.

Multi-agent orchestration supports iterative review and revision through built-in phases that refine results after parallel execution. Separate agents can draft content, review outputs, and produce final reports systematically within the same workflow.

Coordinating research synthesis with parallel agents involves assigning separate agents to gather data, draft sections, and review content. The orchestration system manages these sub-agents through file-based communication, automatically producing a final refined report.

File-based communication in multi-agent orchestration requires explicit input and output file definitions for up to ten sub-agents per stage. This structured approach enforces context protection but limits real-time inter-agent messaging during parallel execution.