iterative-retrieval

To prevent context overload when retrieving codebase information for subagents, apply progressive context retrieval using a structured loop that scores relevance and prunes unnecessary material through phased refinement. This limits cycles to a maximum of three iterations.

The best way to progressively refine context for multi-agent workflows is enforcing a four-phase loop: DISPATCH, EVALUATE, REFINE, and LOOP. This cycle-limited iteration applies relevance scoring to ensure subagents receive only high-quality contextual material.

Handling large repositories with subagents requires iterative retrieval. Start with broad queries, evaluate the gathered context against a relevance threshold, and refine the scope across up to three cycles to prevent context overload and ensure accurate contextual material.

Yes, progressive context retrieval limits the iteration to a maximum of three cycles. This constraint prevents infinite loops during the EVALUATE and REFINE phases, ensuring that context gathering for subagents remains efficient and avoids context overload.

Use iterative retrieval instead of single-pass gathering when subagents require evolving codebase context from large repositories. If the initial context lacks sufficient relevance, the phased refinement loop prunes and gathers more material until the relevance threshold is met.