context-engineering

SKILL.md

Context engineering is the discipline of curating and maintaining the optimal set of tokens during LLM inference. Unlike prompt engineering (crafting individual prompts), context engineering focuses on what information enters the context window and when.

LLMs have limited "attention budgets." As context length increases, models experience context rot—decreased ability to accurately recall information. The goal is finding the smallest possible set of high-signal tokens that maximize desired outcomes.

Key insight: More context isn't better. The right context is better.

AI 에이전트에서 LLM 컨텍스트 창을 효과적으로 관리하기 위한 전략. 긴 대화, 다단계 작업, 도구 조정을 처리하거나 확장된 상호 작용에서 일관성을 유지해야 하는 에이전트를 구축할 때 사용합니다. 출처: itsmostafa/llm-engineering-skills.

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