01Identify and correct 'lost-in-middle' attention patterns
02Apply mitigation strategies for context distraction and confusion
03Detect and recover from context poisoning and compounding errors
04Implement architectural patterns like context partitioning and isolation
05Reference model-specific degradation benchmarks for Claude, GPT, and Gemini
060 GitHub stars