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This paper presents a systematic study on integrating experiential knowledge into LLM tool calling, proposing the KATE framework that combines knowledge-augmented data, width-expanded inference, and knowledge-aware training, achieving consistent improvements on BFCL-V3 and AppWorld benchmarks.