# Prompt Smells: An Omen for Undesirable Generative AI Outputs

arXiv: https://arxiv.org/abs/2401.12611 · HTML: https://mlsanity.com/paper/2401.12611/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 16 references that are in the map.
- First posted on arXiv 23 Jan 2024.

## Builds on (most cited first, 10 of 10)

- [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022)
- [Large Language Models Are Human-Level Prompt Engineers](https://mlsanity.com/paper/2211.01910/) (2022)
- [A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity](https://mlsanity.com/paper/2302.04023/) (2023)
- [A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT](https://mlsanity.com/paper/2302.11382/) (2023)
- [True Few-Shot Learning with Language Models](https://mlsanity.com/paper/2105.11447/) (2021)
- [Design Guidelines for Prompt Engineering Text-to-Image Generative Models](https://mlsanity.com/paper/2109.06977/) (2021)
- [An Introduction to Deep Generative Modeling](https://mlsanity.com/paper/2103.05180/) (2021)
- [Prompt Sapper: A LLM-Empowered Production Tool for Building AI Chains](https://mlsanity.com/paper/2306.12028/) (2023)
- [ChatGPT as a tool for User Story Quality Evaluation: Trustworthy Out of the Box?](https://mlsanity.com/paper/2306.12132/) (2023)
- [RE-centric Recommendations for the Development of Trustworthy(er) Autonomous Systems](https://mlsanity.com/paper/2306.01774/) (2023)

## Built on by (most cited first, 5 of 5)

- [Model Context Protocol (MCP) Tool Descriptions Are Smelly! Towards Improving AI Agent Efficiency with Augmented MCP Tool Descriptions](https://mlsanity.com/paper/2602.14878/) (2026)
- [LLM-Based Social Simulations Require a Boundary](https://mlsanity.com/paper/2506.19806/) (2025)
- [Talking Tennis: Language Feedback from 3D Biomechanical Action Recognition](https://mlsanity.com/paper/2510.03921/) (2025)
- [Specification and Detection of LLM Code Smells](https://mlsanity.com/paper/2512.18020/) (2025)
- [LLM Code Smells: A Taxonomy and Detection Approach](https://mlsanity.com/paper/2605.22976/) (2026)

## Abstract (arXiv)

Recent Generative Artificial Intelligence (GenAI) trends focus on various applications, including creating stories, illustrations, poems, articles, computer code, music compositions, and videos. Extrinsic hallucinations are a critical limitation of such GenAI, which can lead to significant challenges in achieving and maintaining the trustworthiness of GenAI. In this paper, we propose two new concepts that we believe will aid the research community in addressing limitations associated with the application of GenAI models. First, we propose a definition for the "desirability" of GenAI outputs and three factors which are observed to influence it. Second, drawing inspiration from Martin Fowler's code smells, we propose the concept of "prompt smells" and the adverse effects they are observed to have on the desirability of GenAI outputs. We expect our work will contribute to the ongoing conversation about the desirability of GenAI outputs and help advance the field in a meaningful way.