Today's Prompt Engineering: Fastest-Growing Projects — May 20, 2026
Today's the Prompt Engineering space, we've seen a mix of innovative projects ranging from language model writing style adaptation to specialized prompt libraries for various AI platforms. Among these, several repositories have caught our attention due to their rapid growth and significant contributions over the past month. WantongC's "journal-adapt-writing-skill" is one such project that stands out with an impressive Growth Score of 45.83 and a growing community base of nearly 350 stars.
The repository "journal-adapt-writing-skill" aims to help users learn the writing conventions from published journal papers and adapt their manuscripts accordingly, section by section. Its high growth score is likely due to its unique approach to enhancing academic and professional writing quality through AI-driven insights, which has resonated with a wide audience seeking to improve their manuscript submissions.
A-cat-with-carrots' "TypeAnything" offers an intriguing blend of traditional input methods with advanced AI text rewriting capabilities, allowing users to input text in various styles such as English, mixed Chinese-English, financial jargon, internet slang, and even Klingon. With a Growth Score of 15.28 and 50 stars, the project's popularity is growing as it continues to expand its functionality and attract developers interested in integrating AI into everyday tasks.
"Awesome-gpt-image-2," managed by freestylefly, provides an industrial-grade prompt engine and template library for GPT-Image2, featuring over 370 reverse-engineered cases and more than 20 sets of templates. This repository's significant Growth Score of 11.95 and a staggering 5,644 stars indicate its value in the AI image generation community, where developers are actively seeking robust and versatile prompt solutions.
Yaojingang's "yao-open-prompts" is another noteworthy project, offering a comprehensive Chinese AI prompt library that covers various scenarios including work, study, content creation, marketing, and daily life. With 2,172 stars and a Growth Score of 8.48, the repository’s wide applicability across different use cases has undoubtedly contributed to its popularity among users seeking tailored AI assistance.
Anbeeld's "WRITING.md" provides rules for crafting sharper text with specific genre awareness and built-in self-auditing workflows, aiming to enhance the quality of large language model outputs. Its Growth Score of 8.22 and 270 stars suggest that it is gaining traction as a valuable resource for those looking to refine their prompt engineering practices.
"Goal-prompt-builder," developed by win4r, offers tools to build audit-friendly /goal prompts specifically for OpenAI Codex, aiming to improve the transparency of AI-driven workflows. With a Growth Score of 5.11 and 95 stars, it reflects an increasing interest in creating clear and accountable interactions with AI systems.
Chengzhongwei's "Prompt-sensei" provides local-first coaching for Claude Code and Codex, enhancing prompts and analyzing user history to improve prompting habits. This project’s Growth Score of 4.62 and 117 stars indicate its growing importance in the field of personalizing AI interactions for better performance and clarity.
Shiphrahx's "AI-for-engineering-leaders" offers practical playbooks for engineering leaders looking to leverage AI for improved delivery, decision-making, and team productivity through real-world workflows and prompts. Its Growth Score of 3.62 and 49 stars suggest that it is becoming a valuable resource for tech teams interested in integrating AI into their operations.
Bsquang's "claude-comstyle" provides users with the ability to control Claude’s communication style, offering 13 distinct prompts tailored to various preferences and needs. With a Growth Score of 2.94 and 27 stars, it caters specifically to those looking for customization in AI interactions.
Lastly, mturac's "promptguard" audits prompts as behavioral contracts, serving as a pre-write guard for agents that ship code. Its relatively lower Growth Score of 1.37 but still notable presence with 21 stars suggests its niche appeal among developers focused on prompt security and reliability.
These projects collectively highlight the diverse applications and rapid advancements in the field of Prompt Engineering, underscoring the increasing importance of tailored AI interactions across various domains.
The repository "journal-adapt-writing-skill" aims to help users learn the writing conventions from published journal papers and adapt their manuscripts accordingly, section by section. Its high growth score is likely due to its unique approach to enhancing academic and professional writing quality through AI-driven insights, which has resonated with a wide audience seeking to improve their manuscript submissions.
A-cat-with-carrots' "TypeAnything" offers an intriguing blend of traditional input methods with advanced AI text rewriting capabilities, allowing users to input text in various styles such as English, mixed Chinese-English, financial jargon, internet slang, and even Klingon. With a Growth Score of 15.28 and 50 stars, the project's popularity is growing as it continues to expand its functionality and attract developers interested in integrating AI into everyday tasks.
"Awesome-gpt-image-2," managed by freestylefly, provides an industrial-grade prompt engine and template library for GPT-Image2, featuring over 370 reverse-engineered cases and more than 20 sets of templates. This repository's significant Growth Score of 11.95 and a staggering 5,644 stars indicate its value in the AI image generation community, where developers are actively seeking robust and versatile prompt solutions.
Yaojingang's "yao-open-prompts" is another noteworthy project, offering a comprehensive Chinese AI prompt library that covers various scenarios including work, study, content creation, marketing, and daily life. With 2,172 stars and a Growth Score of 8.48, the repository’s wide applicability across different use cases has undoubtedly contributed to its popularity among users seeking tailored AI assistance.
Anbeeld's "WRITING.md" provides rules for crafting sharper text with specific genre awareness and built-in self-auditing workflows, aiming to enhance the quality of large language model outputs. Its Growth Score of 8.22 and 270 stars suggest that it is gaining traction as a valuable resource for those looking to refine their prompt engineering practices.
"Goal-prompt-builder," developed by win4r, offers tools to build audit-friendly /goal prompts specifically for OpenAI Codex, aiming to improve the transparency of AI-driven workflows. With a Growth Score of 5.11 and 95 stars, it reflects an increasing interest in creating clear and accountable interactions with AI systems.
Chengzhongwei's "Prompt-sensei" provides local-first coaching for Claude Code and Codex, enhancing prompts and analyzing user history to improve prompting habits. This project’s Growth Score of 4.62 and 117 stars indicate its growing importance in the field of personalizing AI interactions for better performance and clarity.
Shiphrahx's "AI-for-engineering-leaders" offers practical playbooks for engineering leaders looking to leverage AI for improved delivery, decision-making, and team productivity through real-world workflows and prompts. Its Growth Score of 3.62 and 49 stars suggest that it is becoming a valuable resource for tech teams interested in integrating AI into their operations.
Bsquang's "claude-comstyle" provides users with the ability to control Claude’s communication style, offering 13 distinct prompts tailored to various preferences and needs. With a Growth Score of 2.94 and 27 stars, it caters specifically to those looking for customization in AI interactions.
Lastly, mturac's "promptguard" audits prompts as behavioral contracts, serving as a pre-write guard for agents that ship code. Its relatively lower Growth Score of 1.37 but still notable presence with 21 stars suggests its niche appeal among developers focused on prompt security and reliability.
These projects collectively highlight the diverse applications and rapid advancements in the field of Prompt Engineering, underscoring the increasing importance of tailored AI interactions across various domains.