分析万级开源提示词，发现格式混乱、重复严重等问题，提出管理优化建议。
Understanding Prompt Management in GitHub Repositories: A Call for Best Practices
- 从92个GitHub仓库提取2.48万条提示词，实证研究管理现状
- 发现提示词存在格式不一、大量重复和拼写错误等质量问题
- 为开发者提供可操作的提示词管理最佳实践，助力提示软件生态发展
基础模型（如大语言模型）的快速普及催生了提示软件（promptware），即通过自然语言提示构建的软件。有效的提示管理（如组织与质量保障）至关重要但面临挑战。本研究对来自92个GitHub仓库的24,800个开源提示词进行实证分析，探讨提示管理实践与质量属性。研究发现存在显著的提示格式不一致、内部与外部提示重复率高，以及频繁的可读性与拼写问题。基于这些发现，本文为开发者提供可落地的建议，以提升开源提示词在快速演进的提示软件生态系统中的可用性与可维护性。
原文摘要 · Abstract (English)
The rapid adoption of foundation models (e.g., large language models) has given rise to promptware, i.e., software built using natural language prompts. Effective management of prompts, such as organization and quality assurance, is essential yet challenging. In this study, we perform an empirical analysis of 24,800 open-source prompts from 92 GitHub repositories to investigate prompt management practices and quality attributes. Our findings reveal critical challenges such as considerable inconsistencies in prompt formatting, substantial internal and external prompt duplication, and frequent readability and spelling issues. Based on these findings, we provide actionable recommendations for developers to enhance the usability and maintainability of open-source prompts within the rapidly evolving promptware ecosystem.
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