Skill UI

This skill analyzes the predictable ways language models lose performance as context length increases. It details core patterns, including 'lost-in-middle,' context poisoning, and distraction. Use this knowledge to diagnose unpredictable agent failures, design highly reliable systems for long document processing, and implement advanced context engineering strategies.

This runbook serves as a comprehensive guide for responding to incidents within the OpenEvidence platform. It outlines severity levels (P1-P3), step-by-step triage procedures, and mitigation actions, ensuring rapid and structured resolution of API downtime or degradation issues in a healthcare context.

This skill covers predictable performance degradation patterns in language models as context length increases, including lost-in-middle effects, context poisoning, and distraction. It helps diagnose agent failures and design resilient systems by understanding attention mechanics and context engineering strategies for production environments.