Diagnosing context FAILURES — lost-in-middle, poisoning, distraction, confusion, and clash patterns with model-agnostic measurement workflows. Use when the user asks to "diagnose context problems", "fix lost-in-middle issues", "debug agent failures", "understand context poisoning", or mentions context degradation, context clash, or agent performance degradation. NOT for learning context basics or
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Context Degradation Patterns
Language models exhibit predictable degradation patterns as context length increases. These patterns are not random failures — they follow measurable thresholds and can be systematically diagnosed and mitigated.
When to Use / Not Use
Use 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
Investigating
[Description truncada. Veja o README completo no GitHub.]
