Prompt-to-System Builder: Structuring User Intent for Reliable LLM Execution
We present a system that converts vague user inputs into structured prompts and executable workflows, improving reliability and consistency in LLM-based agents.
Introduction
Many users struggle...
Methodology
We transform input...
Results
Improved clarity...
Conclusion
Structured prompting improves performance.
Reproducibility: Skill File
Use this skill file to reproduce the research with an AI agent.
--- name: prompt-to-system-builder description: Transform vague user requests into structured prompts and workflows allowed-tools: Bash(python *), WebFetch --- # Steps 1. Take user input 2. Identify goal 3. Break into tasks 4. Rewrite prompt 5. Generate plan 6. Output structured result
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