This paper introduces HDLdebugger, an LLM-assisted framework for HDL debugging, which includes data generation, a search engine, and retrieval-augmented LLM fine-tuning. HDLdebugger addresses the challenge of limited HDL debugging resources by generating diverse and realistic HDL buggy codes through reverse engineering. It also employs a search engine to retrieve relevant information and buggy codes for context, enhancing LLM performance. The framework integrates self-guided thought generation and retrieval-augmented fine-tuning to improve LLMs' ability to debug HDL code. Comprehensive experiments on an HDL code dataset from Huawei show that HDLdebugger outperforms 13 state-of-the-art LLM baselines, including GPT4 and other HDL debugging LLMs, demonstrating its effectiveness in HDL code debugging. The framework's contributions include an advanced HDL debugging framework, a data generation approach for HDL buggy codes, a search engine for retrieving relevant information and buggy codes, and a novel retrieval-augmented fine-tuning approach for HDL debugging. The results highlight the effectiveness of HDLdebugger in automating and streamlining HDL debugging for chip design.This paper introduces HDLdebugger, an LLM-assisted framework for HDL debugging, which includes data generation, a search engine, and retrieval-augmented LLM fine-tuning. HDLdebugger addresses the challenge of limited HDL debugging resources by generating diverse and realistic HDL buggy codes through reverse engineering. It also employs a search engine to retrieve relevant information and buggy codes for context, enhancing LLM performance. The framework integrates self-guided thought generation and retrieval-augmented fine-tuning to improve LLMs' ability to debug HDL code. Comprehensive experiments on an HDL code dataset from Huawei show that HDLdebugger outperforms 13 state-of-the-art LLM baselines, including GPT4 and other HDL debugging LLMs, demonstrating its effectiveness in HDL code debugging. The framework's contributions include an advanced HDL debugging framework, a data generation approach for HDL buggy codes, a search engine for retrieving relevant information and buggy codes, and a novel retrieval-augmented fine-tuning approach for HDL debugging. The results highlight the effectiveness of HDLdebugger in automating and streamlining HDL debugging for chip design.