internet-research-orchestrator

Multi-agent research orchestration automates investigation of post-training or unprecedented domains by dynamically allocating 1-7 specialized subagents to perform depth-first, breadth-first, or straightforward analysis, synthesizing results into a coherent, source-attributed report.

Yes. Adaptive orchestration analyzes query novelty and complexity to determine agent allocation, scaling from 1 to 7 subagents and selecting appropriate investigation strategies—depth-first for deep exploration, breadth-first for broad coverage, or straightforward for direct answers.

Phase-based decision logging, self-challenge validation, and session logging to project_logs provide full traceability of orchestration choices, agent assignments, and reasoning steps, enabling reproducibility and governance across research workflows.

TODAS-based orchestration coordinates specialized subagents through novelty assessment and phase-based planning, automatically allocating resources, validating findings through self-challenge, and aggregating parallel results into synthesis—optimized for emerging technologies and rapidly evolving fields.

No. The orchestrator is designed for novel or emerging domains where prior knowledge is minimal. It performs adaptive depth and breadth analysis, novelty detection, and self-challenge validation to handle unprecedented topics without requiring domain expertise upfront.

Yes. Breadth-first and depth-first strategies enable investigation across interdisciplinary domains. Adaptive allocation of 1-7 specialized subagents, combined with comprehensive synthesis, addresses complex queries spanning multiple emerging or novel knowledge areas.