Today's Prompt Engineering: Fastest-Growing Projects — May 30, 2026
Today's the Prompt Engineering space, there's a noticeable trend towards developing versatile and context-aware systems that enhance AI agents' performance across various tasks. The focus on creating intuitive and efficient ways to manage prompts and integrate them into existing workflows is evident as several repositories have seen significant growth and engagement. One standout repository, yaojingang/yao-open-prompts, provides an extensive library of Chinese language AI prompts covering a wide range of scenarios.
yaojingang/yao-open-prompts offers a comprehensive collection of AI prompt templates in Chinese, suitable for various contexts such as work, learning, content creation, marketing, and daily life. With its high growth score of 72.92 and over 2,300 stars, this repository is growing rapidly due to the increasing demand for localized AI solutions that cater specifically to Chinese users.
OnlyTerp/prompt-cache-skills aims to provide drop-in fixes for prompt caching in LLM agent harnesses, ensuring smoother integration with AI coding agents. The project's growth score of 68.00 and steady contribution activity suggest its relevance in addressing practical challenges faced by developers working with large language models.
baskduf/harness-starter-kit is a prompt-first approach to making repositories safer for AI coding agents through a starter kit designed to streamline the initial setup process. Its growth score of 66.12 reflects active development and community interest, likely due to its innovative method of prioritizing prompts in repository security.
open-gsd/gsd-pi introduces a robust system for meta-prompting and context engineering that enables long-term autonomous operation by AI agents without losing focus on the overall goal. With a growth score of 65.81 and over 300 stars, this project is gaining traction due to its comprehensive approach to maintaining agent efficiency and coherence.
OttoRenner/Gentle-Coding explores how authoritarian prompt engineering can induce performance anxiety in LLMs and demonstrates that empathetic framing can mitigate these issues. The repository's lower growth score of 25.00 may be due to its niche focus on understanding and mitigating specific AI behavior anomalies, which attracts a more specialized audience.
WantongC/journal-adapt-writing-skill allows users to learn the writing conventions of any journal from its published papers and adapt their manuscripts accordingly. With over 498 stars, this repository is growing steadily as it addresses the critical need for researchers and writers to adhere to specific publishing guidelines effectively.
zy-zmc/tianming-skill focuses on collaborative long-form novel creation using AI through a modular prompt engineering system tailored specifically for Chinese audiences. The lower growth score of 12.57 might indicate that its specialized nature limits broader appeal, although it still garners interest from enthusiasts in the domain.
A-cat-with-carrots/TypeAnything transforms text input methods by allowing users to type in Pinyin and receive AI-generated output in various styles or languages based on user descriptions. With a growth score of 11.95 and over 200 stars, it is growing due to its unique approach to enhancing writing flexibility and creativity.
majiayu000/awesome-goal-prompts compiles a list of source-backed /goal contracts for coding agents along with seed patterns designed to enhance their functionality. Its growth score of 9.26 reflects consistent development efforts aimed at providing structured guidance for AI tasks, although its niche focus may limit wider adoption.
jnMetaCode/ai-shortfilm-prompts outlines the methodology and prompts used behind a successful short film project created using multiple AI systems. With a growth score of 8.83, it is growing as interest in leveraging AI for creative projects continues to rise, showcasing the potential of integrated prompt engineering techniques in storytelling.
These repositories highlight the dynamic nature of Prompt Engineering, with tools ranging from comprehensive libraries and caching solutions to innovative approaches aimed at enhancing creativity and efficiency across various domains.
yaojingang/yao-open-prompts offers a comprehensive collection of AI prompt templates in Chinese, suitable for various contexts such as work, learning, content creation, marketing, and daily life. With its high growth score of 72.92 and over 2,300 stars, this repository is growing rapidly due to the increasing demand for localized AI solutions that cater specifically to Chinese users.
OnlyTerp/prompt-cache-skills aims to provide drop-in fixes for prompt caching in LLM agent harnesses, ensuring smoother integration with AI coding agents. The project's growth score of 68.00 and steady contribution activity suggest its relevance in addressing practical challenges faced by developers working with large language models.
baskduf/harness-starter-kit is a prompt-first approach to making repositories safer for AI coding agents through a starter kit designed to streamline the initial setup process. Its growth score of 66.12 reflects active development and community interest, likely due to its innovative method of prioritizing prompts in repository security.
open-gsd/gsd-pi introduces a robust system for meta-prompting and context engineering that enables long-term autonomous operation by AI agents without losing focus on the overall goal. With a growth score of 65.81 and over 300 stars, this project is gaining traction due to its comprehensive approach to maintaining agent efficiency and coherence.
OttoRenner/Gentle-Coding explores how authoritarian prompt engineering can induce performance anxiety in LLMs and demonstrates that empathetic framing can mitigate these issues. The repository's lower growth score of 25.00 may be due to its niche focus on understanding and mitigating specific AI behavior anomalies, which attracts a more specialized audience.
WantongC/journal-adapt-writing-skill allows users to learn the writing conventions of any journal from its published papers and adapt their manuscripts accordingly. With over 498 stars, this repository is growing steadily as it addresses the critical need for researchers and writers to adhere to specific publishing guidelines effectively.
zy-zmc/tianming-skill focuses on collaborative long-form novel creation using AI through a modular prompt engineering system tailored specifically for Chinese audiences. The lower growth score of 12.57 might indicate that its specialized nature limits broader appeal, although it still garners interest from enthusiasts in the domain.
A-cat-with-carrots/TypeAnything transforms text input methods by allowing users to type in Pinyin and receive AI-generated output in various styles or languages based on user descriptions. With a growth score of 11.95 and over 200 stars, it is growing due to its unique approach to enhancing writing flexibility and creativity.
majiayu000/awesome-goal-prompts compiles a list of source-backed /goal contracts for coding agents along with seed patterns designed to enhance their functionality. Its growth score of 9.26 reflects consistent development efforts aimed at providing structured guidance for AI tasks, although its niche focus may limit wider adoption.
jnMetaCode/ai-shortfilm-prompts outlines the methodology and prompts used behind a successful short film project created using multiple AI systems. With a growth score of 8.83, it is growing as interest in leveraging AI for creative projects continues to rise, showcasing the potential of integrated prompt engineering techniques in storytelling.
These repositories highlight the dynamic nature of Prompt Engineering, with tools ranging from comprehensive libraries and caching solutions to innovative approaches aimed at enhancing creativity and efficiency across various domains.