sciomc

Parallel research agents run by decomposing a complex goal into 3-7 independent stages, executing them simultaneously, and synthesizing the cross-stage findings into a final reproducible report.

Cross-stage verification is the process of validating findings across independent parallel research stages to ensure accuracy, consistency, and reproducible results before synthesizing the final report.

Yes, AUTO mode enables autonomous execution of parallel scientist agents by utilizing loop control, progress tracking, and session persistence to manage the research workflow without manual intervention.

You decompose research goals by providing explicit objectives alongside defined stage prompts and agent models, which the system then breaks down into independent stages for parallel execution and synthesis.

Session management supports reproducible results by persisting workflow states, tracking progress, and maintaining loop control during autonomous parallel agent execution across multiple research stages.

Parallel scientist agents are not suitable for simple research goals that lack the complexity to benefit from structured decomposition, cross-stage verification, and multi-stage independent parallel execution.