WarpGrep - Fast Subagent for Code Search – Reduces context rot and accelerates coding agents

Summary: WarpGrep is a context subagent that improves coding agent performance by treating context retrieval as a reinforcement learning problem. It speeds up coding tasks by 40% and reduces context rot by 70% on long horizon tasks, enabling more accurate and efficient code search.

What it does

WarpGrep performs parallel grep calls with strict turn budgets and heavy prefill, optimizing context retrieval to maintain high recall without overwhelming models with irrelevant data. It integrates with Claude Code, Codex, OpenCode, or any MCP-compatible coding agent.

Who it's for

It is designed for developers building agentic coding tools that require fast, precise context search across repositories.

Why it matters

WarpGrep addresses slow coding agent performance caused by inefficient context retrieval, reducing hallucinations and improving task accuracy.