Retrieval Optimization Prompt

I'm using RAG (Retrieval-Augmented Generation) for {{use_case}}. My current retrieval pipeline returns {{current_results_count}} chunks but the answers are often {{quality_issue}}.\n\nCurrent setup:\n- Embedding model: {{embedding_model}}\n- Chunk size: {{chunk_size}} tokens\n- Similarity threshold: {{threshold}}\n- Reranking: {{reranking_method}}\n\nDiagnose the likely causes and recommend:\n1. Chunk size adjustments\n2. Query reformulation strategies\n3. Reranking improvements\n4. Hybrid search approaches (semantic + keyword)\n5. Context assembly order (how to arrange retrieved chunks in the prompt)\n6. Evaluation metrics to track improvement