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

Activate this skill when:

• 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

Core Concepts

Structure context placement around the attention U-curve: beginning and end positions receive reliable attention, while middle positions suffer 10-40% reduced recall accuracy (Liu et al., 2023). This is not a model bug but a consequence of attention mechanics — the first token (often BOS) acts as an "attention sink" that absorbs disproportionate attention budget, leaving middle tokens under-attended as context grows.

Treat context poisoning as a circuit breaker problem. Once a hallucination, tool error, or incorrect retrieved fact enters context, it compounds through repeated self-reference. A poisoned goals section causes every downstream decision to reinforce incorrect assumptions. Detection requires tracking claim provenance; recovery requires truncating to before the poisoning point or restarting with verified-only context.