context-degradationlisted

# Context Degradation Patterns Diagnose and fix context failures before they cascade. Context degradation is not binary — it is a continuum that manifests through five distinct, predictable patterns: lost-in-middle, poisoning, distraction, confusion, and clash. Each pattern has specific detection signals and mitigation strategies. Treat degradation as an engineering problem with measurable thresholds, not an unpredictable failure mode. ## When to Activate - Agent performance degrades unexpectedly during long conversations - Debugging cases where agents produce incorrect or irrelevant outputs - Designing systems that must handle large contexts reliably - Evaluating context engineering choices for production systems - Investigating "lost in middle" phenomena in agent outputs - Analyzing context-related failures in agent behavior Do not activate this skill for adjacent work owned by other skills: - Explaining foundational context mechanics without an active failure: `context-fundamentals`. - Applying token-efficiency tactics after the failure pattern is known: `context-optimization`. ## Core Concepts Structure context placement around the attention U-curve: beginning and end positions receive reliable attention, while middle positions suffer materially reduced recall accuracy in long-context experiments (claim-context-degradation-lost-middle-ruler). This is not a model bug but a consequence of attention mechanics — the first token (often BOS) acts as an "attention sink" t