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Code retrieval is central to coding agents. It is the process of sourcing relevant code snippets, documentation, or knowledge from repositories into the context for the agent to make informed actions. Thus, efficient code retrieval could have a major positive impact on the performance of coding agents and the quality of their output. This study delves into different code retrieval techniques, their integration in agentic workflows, and how they enhance coding agent output quality. We compare how human programmers and agents interact with tools, analyze lexical versus semantic search for code retrieval, evaluate retrieval's impact, and review benchmarks focusing on metrics such as latency, tokens, context utilization, and iteration loops. We report takeaways on the effectiveness of different retrieval tools, potential solutions, and opportunities for further research.