Understanding Prompt Management in GitHub Repositories: A Call for Best Practices

2025-09-15

AI Summary

This study identifies pervasive quality deficiencies—including poor formatting consistency, high redundancy, low readability, and frequent spelling errors—in 24,800 open-source prompts on GitHub, severely undermining the usability and maintainability of promptware ecosystems. Method: Leveraging software engineering principles, we conduct a large-scale empirical analysis via automated repository cloning, structured parsing, semantic deduplication, and multi-dimensional quality assessment to systematically characterize current prompt management practices. Contribution/Results: We propose an actionable set of best practices covering standardized metadata schemas, version-controlled management, test-driven development, and documentation standards—and publicly release the corresponding analysis toolchain. This work establishes the first empirically grounded governance framework for prompt engineering, advancing promptware toward standardization, sustainability, and industrial maturity.

Technology Category

• Natural Language Processing: Prompt Engineering / Prompting
• Search and Optimization: Metareasoning and Metaheuristics
• Planning, Routing, and Scheduling: Planning with Language Models

Application Category

• Economics, Online Markets and Human Computation: LLM based quality controls for crowd work
• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

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.

Problem

• Analyzing prompt management practices in GitHub repositories
• Identifying formatting inconsistencies and duplication issues
• Addressing readability and spelling problems in prompts

Innovation

• Empirical analysis of GitHub repositories
• Identified prompt formatting and duplication issues
• Provided actionable recommendations for developers