Research Mode Selection And Workflow Adaptation

Autonomous agent for comprehensive research reports.

Unique: Implements mode-specific workflow orchestration through the ResearchConductor, which adjusts LLM model tier, context compression, and multi-agent iteration counts per mode. This allows a single codebase to serve both fast-and-cheap and thorough-and-expensive research use cases.

vs others: More flexible than fixed-pipeline competitors because mode selection allows users to trade off speed, cost, and quality; more transparent than black-box research tools because mode parameters are explicit and configurable.

via “research mode adaptation with standard/detailed/deep configurations”

An autonomous agent that conducts deep research on any data using any LLM providers

Unique: Implements three explicit research modes (standard/detailed/deep) with mode-specific adjustments to context limits, sub-query count, and revision cycles, rather than single-mode research. Modes are declaratively configured through Config class.

vs others: More flexible than single-mode research because it enables depth control without code changes, and more transparent than automatic depth selection because users explicitly choose their quality-cost tradeoff.