Today's Prompt Engineering: Fastest-Growing Projects — April 18, 2026
Today's Prompt Engineering, we're seeing a surge in repositories focused on optimizing AI coding agents and multimodal prompt injection. The growth of these tools underscores the increasing importance of fine-tuning language models for specific tasks and applications.
repowise-dev/claude-code-prompts (Growth Score: 60.62, Stars: 945) offers independently authored prompt templates for AI coding agents, covering system prompts, tool prompts, agent delegation, memory management, and multi-agent coordination. Its rapid growth can be attributed to its comprehensive coverage of Claude Code's capabilities, making it a go-to resource for developers looking to improve their AI-driven workflows.
amitshekhariitbhu/ai-engineering-interview-questions (Growth Score: 34.52, Stars: 1,072) provides an extensive cheat sheet for AI engineering interviews, featuring questions and answers that help professionals prepare for technical evaluations. With 46 commits in the past month, this repository is growing rapidly due to its relevance in a job market where AI expertise is increasingly valuable.
ShipWithAI/claude-code-mastery (Growth Score: 15.07, Stars: 72) offers a comprehensive free Claude Code course with 16 phases and 55 modules, covering topics from basic to advanced levels. Its growth can be attributed to the increasing demand for in-depth knowledge of AI coding agents like Claude.
ZeroLu/awesome-happy-horse (Growth Score: 10.67, Stars: 57) curates community-driven prompts, news, benchmarks, and sample outputs for the Happy Horse model, serving as a valuable resource hub for developers working with this specific language model. Its growth reflects the expanding user base of the Happy Horse AI.
TaewoooPark/NODEPROMPT (Growth Score: 6.73, Stars: 31) introduces spatial prompt engineering through interactive 3D concept graphs, offering a unique approach to optimizing language models. This repository's growth is driven by interest in innovative methods for improving AI performance.
Josh-blythe/bordair-multimodal (Growth Score: 6.06, Stars: 31) presents an open-source cross-modal and multimodal prompt injection test suite with over 50,500 attack payloads across various modalities. Its growth is fueled by the increasing need for robust security measures in AI systems.
ZeroLu/awesome-gpt-image (Growth Score: 4.45, Stars: 23) collects top-notch GPT Image 2 prompts and examples from leading creators on X, serving as a valuable resource for developers seeking high-quality prompts. This repository's growth is driven by the popularity of GPT Image among AI enthusiasts.
Leonxlnx/agentic-ai-prompt-research (Growth Score: 4.36, Stars: 2,318) delves into research on how agentic AI coding assistants work, including reconstructed prompt patterns and security classification. Although its growth score is relatively low this week, its high star count indicates enduring interest in understanding the inner workings of AI agents.
OuterSpacee/claude-emotion-prompting (Growth Score: 2.80, Stars: 60) offers a research-backed prompting toolkit for Claude grounded in emotion vectors paper by Anthropic. Despite a relatively low growth score, its focused approach to emotional intelligence in AI is attracting attention from developers interested in human-AI interaction.
JonusNattapong/ClaudeCode-Learning (Growth Score: 1.79, Stars: 28) provides resources for learning Claude Code prompt engineering, although its description lacks detail. While it shows modest growth, the potential for more comprehensive documentation could further accelerate its adoption.
repowise-dev/claude-code-prompts (Growth Score: 60.62, Stars: 945) offers independently authored prompt templates for AI coding agents, covering system prompts, tool prompts, agent delegation, memory management, and multi-agent coordination. Its rapid growth can be attributed to its comprehensive coverage of Claude Code's capabilities, making it a go-to resource for developers looking to improve their AI-driven workflows.
amitshekhariitbhu/ai-engineering-interview-questions (Growth Score: 34.52, Stars: 1,072) provides an extensive cheat sheet for AI engineering interviews, featuring questions and answers that help professionals prepare for technical evaluations. With 46 commits in the past month, this repository is growing rapidly due to its relevance in a job market where AI expertise is increasingly valuable.
ShipWithAI/claude-code-mastery (Growth Score: 15.07, Stars: 72) offers a comprehensive free Claude Code course with 16 phases and 55 modules, covering topics from basic to advanced levels. Its growth can be attributed to the increasing demand for in-depth knowledge of AI coding agents like Claude.
ZeroLu/awesome-happy-horse (Growth Score: 10.67, Stars: 57) curates community-driven prompts, news, benchmarks, and sample outputs for the Happy Horse model, serving as a valuable resource hub for developers working with this specific language model. Its growth reflects the expanding user base of the Happy Horse AI.
TaewoooPark/NODEPROMPT (Growth Score: 6.73, Stars: 31) introduces spatial prompt engineering through interactive 3D concept graphs, offering a unique approach to optimizing language models. This repository's growth is driven by interest in innovative methods for improving AI performance.
Josh-blythe/bordair-multimodal (Growth Score: 6.06, Stars: 31) presents an open-source cross-modal and multimodal prompt injection test suite with over 50,500 attack payloads across various modalities. Its growth is fueled by the increasing need for robust security measures in AI systems.
ZeroLu/awesome-gpt-image (Growth Score: 4.45, Stars: 23) collects top-notch GPT Image 2 prompts and examples from leading creators on X, serving as a valuable resource for developers seeking high-quality prompts. This repository's growth is driven by the popularity of GPT Image among AI enthusiasts.
Leonxlnx/agentic-ai-prompt-research (Growth Score: 4.36, Stars: 2,318) delves into research on how agentic AI coding assistants work, including reconstructed prompt patterns and security classification. Although its growth score is relatively low this week, its high star count indicates enduring interest in understanding the inner workings of AI agents.
OuterSpacee/claude-emotion-prompting (Growth Score: 2.80, Stars: 60) offers a research-backed prompting toolkit for Claude grounded in emotion vectors paper by Anthropic. Despite a relatively low growth score, its focused approach to emotional intelligence in AI is attracting attention from developers interested in human-AI interaction.
JonusNattapong/ClaudeCode-Learning (Growth Score: 1.79, Stars: 28) provides resources for learning Claude Code prompt engineering, although its description lacks detail. While it shows modest growth, the potential for more comprehensive documentation could further accelerate its adoption.