system-prompts-and-models-of-ai-tools open source analysis
FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, Lovable, Manus Agent Tools, NotionAI, Orchids.app, Perplexity, Poke, Qoder, Replit, Same.dev, Trae, Traycer AI, VSCode Agent, Warp.dev, Windsurf, Xcode, Z.ai Code, dia & v0. (And other Open Sourced) System Prompts, Internal Tools & AI Models
Project overview
⭐ 98685 · Last activity on GitHub: 2025-11-30
GitHub: https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools
Why it matters for engineering teams
This repository addresses the challenge of integrating and managing system prompts and AI models across diverse development environments. It provides a practical, open source tool for engineering teams focused on machine learning and AI engineering, enabling streamlined access to a wide range of AI assistants and internal tools. Its maturity is reflected in broad adoption and active maintenance, making it a production ready solution for teams looking to embed AI capabilities into their workflows. However, it may not be the best fit for teams seeking a lightweight or single-purpose AI tool, as its extensive scope can introduce complexity and require dedicated resources to manage effectively.
When to use this project
This project is particularly strong when teams need a comprehensive collection of AI prompts and models that integrate with popular development environments like VSCode and GitHub Copilot. Teams should consider alternatives if they require a simpler, more focused AI assistant or have limited capacity to maintain an open source tool for engineering teams with broad AI integration.
Team fit and typical use cases
Machine learning engineers and AI engineering teams benefit most from this repository, using it to enhance coding productivity and automate routine tasks through AI-driven prompts and models. It is commonly employed in products that embed AI-assisted coding, developer tools, and internal automation systems, supporting roles that demand seamless AI integration within established development workflows.
Best suited for
Topics and ecosystem
Activity and freshness
Latest commit on GitHub: 2025-11-30. Activity data is based on repeated RepoPi snapshots of the GitHub repository. It gives a quick, factual view of how alive the project is.