Today's Prompt Engineering: Fastest-Growing Projects — May 17, 2026
This week, the Prompt Engineering space continues to see a steady influx of innovative projects designed to enhance and optimize how AI systems process and generate text. These tools range from comprehensive libraries of prompts tailored for specific use cases to sophisticated software that analyzes and refines prompt effectiveness. One standout project is "awesome-gpt-image-2," which has garnered significant attention with its extensive collection of GPT image generation templates and case studies.
"WantongC/journal-adapt-writing-skill" enables users to learn the writing conventions of various journals by analyzing published papers, then revising their manuscripts accordingly. With a growth score of 59.00 and 277 stars, this tool has seen notable traction as researchers seek to improve the quality and acceptance rates of their academic submissions.
"leanctx," developed by jia-gao, offers a prompt compression solution that reduces token usage in large language model applications without altering existing codebases. This project's growth score of 10.47 and increasing star count reflect its potential to significantly lower costs for developers working with production LLMs.
"yao-open-prompts," created by yaojingang, is a repository of Chinese AI prompts covering various scenarios such as work, study, content creation, marketing, and personal life. With 2,089 stars, this resource library stands out due to its comprehensive coverage and practical applications for users operating in Chinese language environments.
"Anbeeld/WRITING.md" provides guidelines and workflows aimed at making large language model-generated text more precise and genre-specific. The project's growth score of 8.83 indicates a growing interest among developers looking to fine-tune the output quality of AI systems.
"goal-prompt-builder," developed by win4r, is designed to create audit-friendly /goal prompts for OpenAI Codex. Despite its lower growth score of 5.50 and fewer stars (87), it addresses a niche but important requirement in the realm of ethical and transparent AI usage.
"Prompt-sensei" by chengzhongwei functions as a local-first prompt coach for Claude Code and Codex, enhancing prompts and analyzing user habits with explicit consent. With a growth score of 4.80 and 115 stars, it demonstrates potential in the area of personalized AI assistance and feedback.
"AI-for-engineering-leaders," created by shiphrahx, offers practical playbooks for engineering leaders to leverage AI for improved delivery, decision-making, and team productivity. Its growth score of 4.00 suggests that as more teams integrate AI into their workflows, the demand for such guidance will increase.
Lastly, "claude-comstyle" by bsquang provides a set of prompts designed to control Claude's communication style, offering users more flexibility in how they interact with AI systems. With 27 stars and a growth score of 3.20, this project highlights the ongoing trend towards personalized interactions with AI.
These tools collectively underscore the dynamic nature of the Prompt Engineering field, where developers continuously seek ways to optimize AI interaction through better-designed prompts and workflows.
"WantongC/journal-adapt-writing-skill" enables users to learn the writing conventions of various journals by analyzing published papers, then revising their manuscripts accordingly. With a growth score of 59.00 and 277 stars, this tool has seen notable traction as researchers seek to improve the quality and acceptance rates of their academic submissions.
"leanctx," developed by jia-gao, offers a prompt compression solution that reduces token usage in large language model applications without altering existing codebases. This project's growth score of 10.47 and increasing star count reflect its potential to significantly lower costs for developers working with production LLMs.
"yao-open-prompts," created by yaojingang, is a repository of Chinese AI prompts covering various scenarios such as work, study, content creation, marketing, and personal life. With 2,089 stars, this resource library stands out due to its comprehensive coverage and practical applications for users operating in Chinese language environments.
"Anbeeld/WRITING.md" provides guidelines and workflows aimed at making large language model-generated text more precise and genre-specific. The project's growth score of 8.83 indicates a growing interest among developers looking to fine-tune the output quality of AI systems.
"goal-prompt-builder," developed by win4r, is designed to create audit-friendly /goal prompts for OpenAI Codex. Despite its lower growth score of 5.50 and fewer stars (87), it addresses a niche but important requirement in the realm of ethical and transparent AI usage.
"Prompt-sensei" by chengzhongwei functions as a local-first prompt coach for Claude Code and Codex, enhancing prompts and analyzing user habits with explicit consent. With a growth score of 4.80 and 115 stars, it demonstrates potential in the area of personalized AI assistance and feedback.
"AI-for-engineering-leaders," created by shiphrahx, offers practical playbooks for engineering leaders to leverage AI for improved delivery, decision-making, and team productivity. Its growth score of 4.00 suggests that as more teams integrate AI into their workflows, the demand for such guidance will increase.
Lastly, "claude-comstyle" by bsquang provides a set of prompts designed to control Claude's communication style, offering users more flexibility in how they interact with AI systems. With 27 stars and a growth score of 3.20, this project highlights the ongoing trend towards personalized interactions with AI.
These tools collectively underscore the dynamic nature of the Prompt Engineering field, where developers continuously seek ways to optimize AI interaction through better-designed prompts and workflows.