customaize-agent:prompt-engineering

Advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability.

Teach the model by showing examples instead of explaining rules. Include 2-5 input-output pairs that demonstrate the desired behavior. Use when you need consistent formatting, specific reasoning patterns, or handling of edge cases. More examples improve accuracy but consume tokens—balance based on task complexity.

Request step-by-step reasoning before the final answer. Add "Let's think step by step" (zero-shot) or include example reasoning traces (few-shot). Use for complex problems requiring multi-step logic, mathematical reasoning, or when you need to verify the model's thought process. Improves accuracy on analytical tasks by 30-50%.

프롬프트 최적화, LLM 출력 개선 또는 프로덕션 프롬프트 템플릿 디자인을 포함하여 에이전트용 명령, 후크, 스킬, 하위 에이전트용 프롬프트 또는 기타 LLM 상호 작용을 작성할 때 이 스킬을 사용하십시오. 출처: neolabhq/context-engineering-kit.