Compress an agent's context — long environment observations and accumulated interaction history — on long-horizon tasks using Microsoft's ACON method: threshold-triggered LLM compression with guidelines optimized from contrastive failure analysis. Trigger when an agent loop's context grows across many tool-call steps and blows token budgets or degrades decisions, when designing what a summarizer/compressor must preserve, or when distilling a compressor into a smaller model.
