Today's Prompt Engineering: Fastest-Growing Projects — May 29, 2026
Today's Prompt Engineering, we've seen a diverse range of projects gaining traction on GitHub, from comprehensive Chinese AI prompt libraries to innovative systems that leverage context engineering for autonomous agent tasks. Yaojingang's yao-open-prompts stands out as the most notable project this week, with significant growth and community engagement.
yaojingang/yao-open-prompts is a repository containing a collection of Chinese AI prompts covering various scenarios such as work, study, content creation, marketing, and daily life. With a Growth Score of 75.70 and over 2,315 stars, the project's popularity reflects its comprehensive coverage and practical application in multiple domains.
open-gsd/gsd-pi offers a powerful meta-prompting system designed to enable agents to operate autonomously for extended periods without losing context or focus. This repository has seen high activity with 100 commits over the past month, contributing to its strong growth score of 73.36 and growing community interest.
OttoRenner/Gentle-Coding is a proof-of-concept project exploring how authoritarian prompt engineering can induce performance anxiety in LLM reasoning frameworks and demonstrating that empathetic framing can mitigate these issues. The project's unique approach to ethical AI development, with 35.00 Growth Score and 59 stars, has garnered attention from researchers interested in the psychological impact of AI prompts.
WantongC/journal-adapt-writing-skill is a tool designed to help authors adapt their writing style to match specific journal conventions by analyzing published papers. With a growth score of 22.81 and 490 stars, this project highlights the practical application of prompt engineering in academic publishing workflows.
zy-zmc/tianming-skill introduces a modular prompting system for collaborative AI-driven novel writing, tailored specifically for the Claude Skill platform. Despite its modest growth score of 13.83, the project's unique focus on creative collaboration and storytelling has attracted a small but engaged community.
A-cat-with-carrots/TypeAnything is an innovative input method that uses Weasel TSF and librime to transform user inputs into various writing styles with AI assistance. The tool's versatility in supporting diverse linguistic styles, combined with its growth score of 12.58 and 205 stars, positions it as a creative solution for writers.
jnMetaCode/ai-shortfilm-prompts provides methodologies and prompts used to create the award-winning short film "Zombie Scavenger," showcasing how AI can be harnessed in filmmaking. With its growth score of 9.23 and 65 stars, this project offers insights into the creative use of AI prompts for cinematic storytelling.
OnlyTerp/prompt-cache-skills introduces a drop-in solution to optimize prompt caching for LLM agents, enhancing their efficiency and performance. The repository's active development with 31 commits in the past month, alongside its growth score of 6.30 and 66 stars, underscores its relevance in improving AI agent workflows.
win4r/goal-prompt-builder focuses on generating audit-friendly /goal prompts for OpenAI Codex to ensure compliance and transparency in AI-driven coding tasks. Though it has a relatively lower growth score of 4.06 and only 138 stars, the project's niche focus on ethical development practices makes it valuable within specific use cases.
Today's trends highlight both the breadth and depth of innovation in prompt engineering across various applications, from creative writing to academic publishing, showcasing the growing importance of context-aware prompts for enhancing AI performance.
yaojingang/yao-open-prompts is a repository containing a collection of Chinese AI prompts covering various scenarios such as work, study, content creation, marketing, and daily life. With a Growth Score of 75.70 and over 2,315 stars, the project's popularity reflects its comprehensive coverage and practical application in multiple domains.
open-gsd/gsd-pi offers a powerful meta-prompting system designed to enable agents to operate autonomously for extended periods without losing context or focus. This repository has seen high activity with 100 commits over the past month, contributing to its strong growth score of 73.36 and growing community interest.
OttoRenner/Gentle-Coding is a proof-of-concept project exploring how authoritarian prompt engineering can induce performance anxiety in LLM reasoning frameworks and demonstrating that empathetic framing can mitigate these issues. The project's unique approach to ethical AI development, with 35.00 Growth Score and 59 stars, has garnered attention from researchers interested in the psychological impact of AI prompts.
WantongC/journal-adapt-writing-skill is a tool designed to help authors adapt their writing style to match specific journal conventions by analyzing published papers. With a growth score of 22.81 and 490 stars, this project highlights the practical application of prompt engineering in academic publishing workflows.
zy-zmc/tianming-skill introduces a modular prompting system for collaborative AI-driven novel writing, tailored specifically for the Claude Skill platform. Despite its modest growth score of 13.83, the project's unique focus on creative collaboration and storytelling has attracted a small but engaged community.
A-cat-with-carrots/TypeAnything is an innovative input method that uses Weasel TSF and librime to transform user inputs into various writing styles with AI assistance. The tool's versatility in supporting diverse linguistic styles, combined with its growth score of 12.58 and 205 stars, positions it as a creative solution for writers.
jnMetaCode/ai-shortfilm-prompts provides methodologies and prompts used to create the award-winning short film "Zombie Scavenger," showcasing how AI can be harnessed in filmmaking. With its growth score of 9.23 and 65 stars, this project offers insights into the creative use of AI prompts for cinematic storytelling.
OnlyTerp/prompt-cache-skills introduces a drop-in solution to optimize prompt caching for LLM agents, enhancing their efficiency and performance. The repository's active development with 31 commits in the past month, alongside its growth score of 6.30 and 66 stars, underscores its relevance in improving AI agent workflows.
win4r/goal-prompt-builder focuses on generating audit-friendly /goal prompts for OpenAI Codex to ensure compliance and transparency in AI-driven coding tasks. Though it has a relatively lower growth score of 4.06 and only 138 stars, the project's niche focus on ethical development practices makes it valuable within specific use cases.
Today's trends highlight both the breadth and depth of innovation in prompt engineering across various applications, from creative writing to academic publishing, showcasing the growing importance of context-aware prompts for enhancing AI performance.