How to combine user intent with content structure in prompt design to achieve precise matching?

The core of achieving precise matching between user intent and content structure when designing prompts lies in first clarifying the hierarchy of user intent (such as information inquiry, task execution, or creative needs), and then constructing a structured framework that matches the intent. For information inquiry intent (e.g., "how to optimize prompts"), a "question-core elements-examples" structure is suitable to highlight key information; for task execution intent (e.g., "generate marketing copy"), it is necessary to include "target scenario-constraints-output format" to ensure clear instructions; for creative intent (e.g., "write a story opening"), a guided structure with reserved creative space is required. It is recommended to first extract the core intent through user behavior data, and then organize the prompt structure according to "intent type-information priority-logical order", which can improve matching accuracy. In daily optimization, you can test the impact of different structures on output effects and gradually adjust to fit users' real needs.