Today's Prompt Engineering: Fastest-Growing Projects — May 15, 2026
Today's Prompt Engineering, we've seen a diverse range of projects emerging to cater to various needs, from refining writing skills for academic journals to creating industrial-grade templates for image generation with GPT models. The most notable project is WantongC’s journal-adapt-writing-skill, which has garnered significant attention due to its innovative approach in helping users adapt their manuscripts to match the writing conventions of specific journals.
WantongC/journal-adapt-writing-skill helps learners understand and adopt the writing styles of various academic journals by analyzing published papers. Its high growth score of 76.75 and 163 stars indicate a strong community interest, likely due to its practical application in academia and research.
Freestylefly/awesome-gpt-image-2 is an extensive library offering over 370 reverse-engineered cases and more than 20 industrial-grade templates for generating images with GPT models. The project's robust growth, reflected in a steady stream of commits (96 in the last month) and its impressive star count of 5,319, underscores its utility in the image generation space.
Jia-gao’s leanctx is designed to compress prompts for production LLM applications, reducing token usage by up to 40-60% without altering existing code. This project's growth score of 10.65 and 206 stars suggest that developers are actively seeking efficient ways to manage costs while maintaining performance in LLM projects.
Yaojingang/yao-open-prompts is a comprehensive collection of Chinese AI prompts covering various scenarios such as work, study, content creation, marketing, and daily life. With its growth score of 10.51 and 2,024 stars, this repository demonstrates the growing demand for localized AI solutions tailored to specific cultural contexts.
Anbeeld/WRITING.md outlines rules for crafting sharper and genre-aware text using LLMs, emphasizing concrete anchors and self-auditing workflows. Its growth score of 9.67 and 265 stars highlight its value in enhancing the quality and specificity of generated content.
Win4r’s goal-prompt-builder is a tool designed to create audit-friendly /goal prompts for OpenAI Codex. With a modest but steady increase in popularity, reflected by its growth score of 6.10 and 77 stars, it addresses a specific need within the developer community for more transparent and auditable AI interactions.
Chengzhongwei’s Prompt-sensei serves as a local-first prompt coach for Claude Code and Codex, enhancing prompts and analyzing user habits with explicit consent. Its growth score of 5.30 and 116 stars suggest that there is an increasing interest in tools that provide personalized feedback and improvement for AI interactions.
Shiphrahx’s AI-for-engineering-leaders provides practical playbooks aimed at improving team productivity, delivery, and decision-making through the use of real workflows and prompts. With a growth score of 4.47 and 47 stars, this project is gaining traction among engineering leaders looking to integrate AI into their teams more effectively.
Bsquang’s claude-comstyle offers 13 different prompts designed to control how Claude communicates by choosing from various styles that reduce noise in interactions. Its modest growth score of 3.50 and 27 stars indicate a niche but growing interest among users seeking tailored communication styles for AI conversations.
These projects collectively illustrate the breadth and depth of innovation happening within the Prompt Engineering space, catering to diverse needs across industries and use cases.
WantongC/journal-adapt-writing-skill helps learners understand and adopt the writing styles of various academic journals by analyzing published papers. Its high growth score of 76.75 and 163 stars indicate a strong community interest, likely due to its practical application in academia and research.
Freestylefly/awesome-gpt-image-2 is an extensive library offering over 370 reverse-engineered cases and more than 20 industrial-grade templates for generating images with GPT models. The project's robust growth, reflected in a steady stream of commits (96 in the last month) and its impressive star count of 5,319, underscores its utility in the image generation space.
Jia-gao’s leanctx is designed to compress prompts for production LLM applications, reducing token usage by up to 40-60% without altering existing code. This project's growth score of 10.65 and 206 stars suggest that developers are actively seeking efficient ways to manage costs while maintaining performance in LLM projects.
Yaojingang/yao-open-prompts is a comprehensive collection of Chinese AI prompts covering various scenarios such as work, study, content creation, marketing, and daily life. With its growth score of 10.51 and 2,024 stars, this repository demonstrates the growing demand for localized AI solutions tailored to specific cultural contexts.
Anbeeld/WRITING.md outlines rules for crafting sharper and genre-aware text using LLMs, emphasizing concrete anchors and self-auditing workflows. Its growth score of 9.67 and 265 stars highlight its value in enhancing the quality and specificity of generated content.
Win4r’s goal-prompt-builder is a tool designed to create audit-friendly /goal prompts for OpenAI Codex. With a modest but steady increase in popularity, reflected by its growth score of 6.10 and 77 stars, it addresses a specific need within the developer community for more transparent and auditable AI interactions.
Chengzhongwei’s Prompt-sensei serves as a local-first prompt coach for Claude Code and Codex, enhancing prompts and analyzing user habits with explicit consent. Its growth score of 5.30 and 116 stars suggest that there is an increasing interest in tools that provide personalized feedback and improvement for AI interactions.
Shiphrahx’s AI-for-engineering-leaders provides practical playbooks aimed at improving team productivity, delivery, and decision-making through the use of real workflows and prompts. With a growth score of 4.47 and 47 stars, this project is gaining traction among engineering leaders looking to integrate AI into their teams more effectively.
Bsquang’s claude-comstyle offers 13 different prompts designed to control how Claude communicates by choosing from various styles that reduce noise in interactions. Its modest growth score of 3.50 and 27 stars indicate a niche but growing interest among users seeking tailored communication styles for AI conversations.
These projects collectively illustrate the breadth and depth of innovation happening within the Prompt Engineering space, catering to diverse needs across industries and use cases.