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Scop provides the following specific methods to solve the problem of vague prompt commands:
- Structured target inputWhen generating prompts, the system requires users to fill in the "Objective" (e.g., "Write a cell phone product copy that contains 3 selling points"), "Model", and "Use Case" elements. The system requires users to fill in the three elements of "objective" (e.g. "write a mobile phone product copy with 3 selling points"), "model" and "use case".
- Parameter adjustment function: Adjust the level of detail of the prompt via the visualization slider; to the left is a succinct instruction, to the right will increase the detail required (e.g. word count and formatting).
- Real-time preview mechanism: Immediately after generation, you can view the effect of different models responding to the prompts, and support iterative adjustments until the output meets expectations.
Operation Suggestion: For critical tasks, it is recommended to first generate 3-5 versions of prompts with different levels of detail using free credits, and choose the best solution by previewing and comparing them.
This answer comes from the articleScop: a tool to quickly generate and optimize AI system tipsThe
May not be reproduced without permission:AI productivity tools " How to solve the problem of low output quality due to ambiguous AI model prompt commands?
