context-degradation

Solid

This skill should be used for diagnosing and mitigating context degradation: lost-in-middle failures, context poisoning, context clash, context confusion, attention-pattern issues, and agent performance degradation caused by accumulated or conflicting context.

AI & Automation 18 stars 1 forks Updated today Apache-2.0

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Description 5%
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Skill Content

# 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 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`. - Designing a compression or handoff summary strategy: `context-compression`. - Persisting large outputs, logs, or scratch state outside the prompt: `filesystem-context`. ## 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 ...

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Author
docxology
Repository
docxology/template
Created
11 months ago
Last Updated
today
Language
Python
License
Apache-2.0

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