Context Degradation
技能 活跃This skill should be used when the user asks to "diagnose context problems", "fix lost-in-middle issues", "debug agent failures", "understand context poisoning", or mentions context degradation, attention patterns, context clash, context confusion, or agent performance degradation. Provides patterns for recognizing and mitigating context failures.
To help developers and users understand, diagnose, and fix context-related performance issues in LLM agents, ensuring more reliable and predictable agent behavior.
功能
- Diagnose context degradation patterns (lost-in-middle, poisoning, distraction, confusion, clash)
- Provides detection signals and mitigation strategies
- Explains attention mechanics and context placement impact
- Offers practical guidance via a four-bucket framework and architectural patterns
- Includes concrete examples and research-backed insights
使用场景
- Debugging agent failures due to context issues
- Optimizing agent performance in long conversations
- Designing resilient LLM systems for production
- Understanding and mitigating 'lost in the middle' phenomena
非目标
- Replacing core LLM functionalities
- Providing specific tool implementations
- Addressing prompt engineering issues unrelated to context limits
实践
- Context Engineering
- LLM Agent Design
- Debugging
- Performance Optimization
Trust
- warning:Issues AttentionThere are 6 open issues and 2 closed issues in the last 90 days, indicating a low closure rate (<10%) and potentially slow maintainer response.
安装
请先添加 Marketplace
/plugin marketplace add muratcankoylan/Agent-Skills-for-Context-Engineering/plugin install Agent-Skills-for-Context-Engineering@context-engineering-marketplace质量评分
类似扩展
Context Compression
100This skill should be used when the user asks to "compress context", "summarize conversation history", "implement compaction", "reduce token usage", or mentions context compression, structured summarization, tokens-per-task optimization, or long-running agent sessions exceeding context limits.
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