iterative-retrieval

Iterative retrieval progressively gathers and refines codebase context using a 4-phase loop: DISPATCH, EVALUATE, REFINE, and LOOP, running up to three cycles to narrow down relevant files for subagents.

Reducing token usage in multi-agent code exploration is achieved by iteratively refining retrieved files through up to three cycles, optimizing context gathering before subagents begin execution.

Iterative retrieval in RAG workflows works by dispatching initial context, evaluating relevance, refining the file selection, and looping the process up to three times to iteratively narrow down the most relevant codebase context.

Yes, the iterative context retrieval process is configurable with a maximum of three cycles, allowing you to balance context depth and performance in multi-agent orchestration and code exploration tasks.

You need iterative context gathering when subagents lack required context until they begin work, requiring progressively refined retrieved material to improve task success in uncertain codebase contexts.

Yes, it integrates with AI agents to optimize context gathering in multi-agent workflows, progressively refining retrieved material to reduce token usage and improve task success in uncertain contexts.