What the Project Is
The repository x1xhlol/system-prompts-and-models-of-ai-tools is a collection of system prompts, internal tools, and AI models associated with a variety of AI-powered development and productivity applications. It includes materials linked to tools such as Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, Lovable, Manus, NotionAI, Orchids.app, Perplexity, Poke, Qoder, Replit, Same.dev, Trae, Traycer AI, VSCode Agent, Warp.dev, Windsurf, Xcode, Z.ai Code, Dia, and v0, among others. The project describes itself as offering “FULL” access to these components, positioning the repository as a centralized source for insights into how these AI tools are configured and operated.
Why It Is Gaining Attention
The repository has attracted significant attention, as reflected by its high number of stars on GitHub. This interest appears to stem from the growing curiosity among developers and tech enthusiasts about the inner workings of popular AI-assisted coding and productivity tools. As these tools become more integrated into software development workflows, there is increasing demand to understand their underlying prompts and behaviors—both for learning purposes and to assess potential risks or opportunities for customization. The project taps into this interest by aggregating what it claims are the system prompts and models used by these services.
How It Works at a High Level
The repository functions as a curated collection of text-based assets, primarily system prompts and related configuration files, that are presented as corresponding to specific AI tools. These prompts typically define the behavior, role, and constraints of an AI model when interacting with users—such as instructing it to act as a coding assistant, follow certain safety guidelines, or adhere to a particular interaction style. By making these prompts accessible, the repository allows users to inspect, compare, and study how different AI tools are tuned for specific tasks. The project does not appear to host or distribute the actual AI models themselves, but rather focuses on the textual instructions that guide model behavior.
Who It Is For and Real Use Cases
The project is aimed at developers, AI researchers, and technically curious individuals who want to understand how AI-powered tools are configured. Potential use cases include reverse-engineering tool behavior for educational purposes, improving prompt engineering skills, identifying patterns in AI alignment or safety measures, and exploring ways to replicate or adapt certain functionalities in personal or open-source projects. It may also serve security-conscious users who wish to audit whether sensitive system information is inadvertently exposed through prompt leakage—a concern highlighted in the repository’s own security notice.
Honest Caveats
Several important limitations and risks are evident from the repository’s own disclaimers. The project includes a explicit security notice warning AI startups that exposed prompts or models can become targets for hackers, and it promotes a third-party service (ZeroLeaks) for securing AI systems against prompt injection and extraction risks. This suggests the project’s operators are aware of the sensitivity of the material they are sharing. Additionally, the repository’s roadmap section notes only that users should “Open an issue” for feedback, with a latest update date of 12/07/2026, indicating ongoing maintenance but offering little detail about version control, support commitments, or long-term sustainability. The licensing status of the collected prompts and models is not specified in the README, raising questions about legal reuse, especially given that many of the source tools are likely proprietary. Users should exercise caution regarding potential copyright or terms-of-service violations when accessing or using this material.
Source: https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools
