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system prompts and models of ai tools

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Basic Information

This repository is a curated, public collection of system prompts, model configurations and example tools used by many open and closed AI agents. It aggregates prompt sets and related files for platforms and projects such as Cursor, Manus, Same.dev, Lovable, Devin, Replit Agent, Windsurf Agent, VSCode Agent, Dia Browser, Trae AI, Cluely, Perplexity, Xcode, Spawn, Orchids.app and other open sourced system prompts and models. The README lists a large table of contents with per-project folders, notes that the collection comprises over 9000+ lines of insights, and points readers to a Discord for early releases and discussion. The repository is positioned as a research and reference resource rather than an executable framework. It includes donation and sponsorship information, a security notice for AI startups, a roadmap section asking users to open issues, and a visible folder structure organizing prompts, tools and open source examples.

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App URL
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools
Github Repository
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools/blob/main/README.md

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App Details

Features
Organized folders for many agent projects and prompt sets, including dedicated directories for v0 prompts, Spawn, Manus, Lovable, Devin, Same.dev, Replit, Windsurf, VSCode, Cursor, Dia, Trae, Perplexity, Cluely, Xcode, Orchids.app and more. A long-form README with a table of contents, star history badge and charts, and a note that the collection contains 9000+ lines of material. Community features include a Discord channel for early access and discussion, a roadmap and feedback instructions via issues, and sponsor/donation options. Metadata and structure emphasize discoverability with subfolders for open source prompts and example tools. There is also a security notice aimed at startups and a recommendation to use an external audit service. The repo is maintained and updated with commit history and update timestamps.
Use Cases
This repository helps researchers, prompt engineers and developers understand how different AI agents are instructed and configured by exposing real-world system prompts and model files side by side. Users can compare prompt styles across platforms, reuse or adapt templates, study agent behavior patterns, and gather examples for prompt engineering experiments. It aids security-conscious teams by highlighting the risks of leaked prompts and pointing to auditing advice. The foldered layout and documentation make it straightforward to find agent-specific prompts or open source examples to fork or adapt. Community channels and an issues-based roadmap let contributors request additions or report problems, making it useful as a living reference and learning resource rather than a turnkey agent framework.

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