Today's Prompt Engineering: Fastest-Growing Projects — May 25, 2026
Today's the Prompt Engineering space, we see a continued surge of interest in repositories that cater to diverse applications such as academic writing, novel creation, and input method utilities for AI-driven text transformation. Among these, Yaojingang's "yao-open-prompts" stands out with an impressive growth score and a wide range of use cases.
*yaojingang/yao-open-prompts* is a repository containing a Chinese AI prompt library that covers various scenarios including work, study, content creation, marketing, and daily life. With a growth score of 89.26 and over 2,000 stars, the project's rapid rise can be attributed to its comprehensive coverage and localization for a specific language community.
*WantongC/journal-adapt-writing-skill* aims at helping authors learn and adapt to the writing conventions of different journals from their published papers, thereby improving manuscript quality. This repository has gained 27.17 growth points with 424 stars, suggesting that it addresses a critical need for academic writers looking to refine their submissions.
*zmc/zy-zmc/tianming-skill* offers a modular prompt engineering system specifically designed for collaborative long-form novel writing with AI assistance. The project's moderate growth score of 23 and fewer than 50 stars indicate a niche but growing interest among creative writers leveraging AI for narrative development.
*A-cat-with-carrots/TypeAnything* is an innovative Windows input method that allows users to type in Chinese pinyin and have the text automatically transformed into various styles, including English, academic jargon, or even Klingon. With 131 stars and a growth score of 13.17, its unique feature set attracts developers interested in AI-driven language transformation tools.
*huck012428-lab/prompt-atlas* curates prompt cards for large language model trainers, product managers, and evaluation teams to streamline their processes with structured guidance. The repository's solid growth score of 10.53 and 136 stars suggest a growing need for standardized prompts across different AI development roles.
*jnMetaCode/ai-shortfilm-prompts* provides the methodology and prompts used in creating "Zombie Scavenger," an AI-generated short film that received critical acclaim. With a growth score of 10.14 and 37 stars, it highlights the potential for AI to innovate storytelling formats through precise prompt engineering.
*open-gsd/gsd-pi* presents a sophisticated system aimed at enabling agents to operate autonomously over extended periods while maintaining focus on overarching goals. The project's high growth score of 8.97 and 131 stars reflect its appeal to developers looking for advanced context management and meta-prompting capabilities.
*win4r/goal-prompt-builder* focuses on developing audit-friendly /goal prompts specifically tailored for the OpenAI Codex. With a lower but still noteworthy growth score of 4.35 and 120 stars, it caters to those in need of precise and transparent prompt creation tools for AI-driven code generation tasks.
*shiphrahx/AI-for-engineering-leaders* offers practical AI playbooks designed to enhance decision-making and team productivity within engineering teams. Although its growth score is relatively low at 2.87, the repository garners interest from leaders looking to integrate AI into their workflows with real-world examples and guidance.
*mtrac/promptguard* audits prompts as behavioral contracts before agents ship code, ensuring that they adhere to predefined rules and behaviors. With a modest but steady growth score of 1.47 and 43 stars, it serves developers concerned about the ethical implications and reliability of AI-generated content.
Today's report showcases an array of innovative applications of prompt engineering across various domains, from creative writing and academic publishing to software development and team management, reflecting a growing recognition of its potential in enhancing productivity and creativity.
*yaojingang/yao-open-prompts* is a repository containing a Chinese AI prompt library that covers various scenarios including work, study, content creation, marketing, and daily life. With a growth score of 89.26 and over 2,000 stars, the project's rapid rise can be attributed to its comprehensive coverage and localization for a specific language community.
*WantongC/journal-adapt-writing-skill* aims at helping authors learn and adapt to the writing conventions of different journals from their published papers, thereby improving manuscript quality. This repository has gained 27.17 growth points with 424 stars, suggesting that it addresses a critical need for academic writers looking to refine their submissions.
*zmc/zy-zmc/tianming-skill* offers a modular prompt engineering system specifically designed for collaborative long-form novel writing with AI assistance. The project's moderate growth score of 23 and fewer than 50 stars indicate a niche but growing interest among creative writers leveraging AI for narrative development.
*A-cat-with-carrots/TypeAnything* is an innovative Windows input method that allows users to type in Chinese pinyin and have the text automatically transformed into various styles, including English, academic jargon, or even Klingon. With 131 stars and a growth score of 13.17, its unique feature set attracts developers interested in AI-driven language transformation tools.
*huck012428-lab/prompt-atlas* curates prompt cards for large language model trainers, product managers, and evaluation teams to streamline their processes with structured guidance. The repository's solid growth score of 10.53 and 136 stars suggest a growing need for standardized prompts across different AI development roles.
*jnMetaCode/ai-shortfilm-prompts* provides the methodology and prompts used in creating "Zombie Scavenger," an AI-generated short film that received critical acclaim. With a growth score of 10.14 and 37 stars, it highlights the potential for AI to innovate storytelling formats through precise prompt engineering.
*open-gsd/gsd-pi* presents a sophisticated system aimed at enabling agents to operate autonomously over extended periods while maintaining focus on overarching goals. The project's high growth score of 8.97 and 131 stars reflect its appeal to developers looking for advanced context management and meta-prompting capabilities.
*win4r/goal-prompt-builder* focuses on developing audit-friendly /goal prompts specifically tailored for the OpenAI Codex. With a lower but still noteworthy growth score of 4.35 and 120 stars, it caters to those in need of precise and transparent prompt creation tools for AI-driven code generation tasks.
*shiphrahx/AI-for-engineering-leaders* offers practical AI playbooks designed to enhance decision-making and team productivity within engineering teams. Although its growth score is relatively low at 2.87, the repository garners interest from leaders looking to integrate AI into their workflows with real-world examples and guidance.
*mtrac/promptguard* audits prompts as behavioral contracts before agents ship code, ensuring that they adhere to predefined rules and behaviors. With a modest but steady growth score of 1.47 and 43 stars, it serves developers concerned about the ethical implications and reliability of AI-generated content.
Today's report showcases an array of innovative applications of prompt engineering across various domains, from creative writing and academic publishing to software development and team management, reflecting a growing recognition of its potential in enhancing productivity and creativity.