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This paper presents ZhuLong, an execution-grounded LLM coding agent for EDA scripting that uses API retrieval, documentation inspection, and sandbox execution via MCP tools, augmented by an offline API self-exploration mechanism to infer undocumented API behaviors. It achieves 78.5% Pass@1 on a benchmark of 158 real-world EDA tasks, significantly outperforming a pure LLM baseline.
A community member shares their hands-on experience generating a track using Google's Lyria 3 Pro via its API, noting the minimal cost and initial quality of the output.