x1xhlol/system-prompts-and-models-of-ai-tools

⭐ 136,967  ·  #2  ·  N/A

FULL 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 & v0. (And other Open Sourced) System Prompts, Internal Tools & AI Models

ai bolt cluely Skill

Project Analysis

🎯 Positioning	Agent capability enhancement
💡 Core Value	Provides standardized Skills and Prompt templates for AI coding Agents, covering specific scenarios (code review, debugging, architecture design, etc.), enabling Agents to produce higher quality output in these scenarios
👥 Target Audience	Developers using Agent tools like Claude Code/Cursor/Codex, aiming to improve Agent performance on specific tasks

Why It's Worth Attention

The scale of 136,967 Stars on GitHub indicates this is a leading project in this direction, with high community recognition. Core feature: Cryptocurrency:.

In-Depth AI Analysis Report

Alright, as a senior technical editor, I will conduct an in-depth analysis of the x1xhlol/system-prompts-and-models-of-ai-tools project.

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One-Sentence Summary

A public resource repository aggregating system prompts and models from mainstream AI tools.

Core Features

This project is essentially an "Awesome List" type of resource aggregation library, whose core value lies in the collection, organization, and public disclosure of information. Key features include:

1. Broad Coverage of AI Tools: Collects System Prompts from over 20 mainstream AI coding, AI agent, and AI application tools, including Cursor, Devin, GitHub Copilot, Perplexity, Replit, Windsurf, Trae, v0, and more.
2. Leaked Prompts and Model Files: The project's core content involves obtaining and publicly disclosing "system prompts" and some internal model files from various AI tools through methods like reverse engineering, public leaks, and community contributions, revealing the operational logic and instruction sets behind these AI tools.
3. Mix of Open Source and Proprietary Models: The content includes not only prompts for open-source models but also focuses on proprietary prompts and internal tool information from closed-source commercial AI tools, offering significant "unveiling" value.
4. Community-Driven Update Mechanism: The project interacts with the community via Discord and GitHub Issues, continuously updating content, and has sponsors and donation channels to support maintenance.

Technical Architecture

This project is not a runnable software or framework, but a pure document/file collection. Therefore, its "technical architecture" is reflected in the organization of its content:

• Tech Stack: No specific tech stack. Primarily uses Markdown (*.md) and plain text files for content storage, organized by directory structure.
• Code Structure Highlights:
  • Directory Structure by Tool: Creates independent folders for each AI tool under the root directory (e.g., cursor/, devin/), with a clear structure for easy searching.
  • README.md as Navigation: The main README file lists all included tools and links to their corresponding directories, serving as an index map for the entire repository.
  • Sponsor Integration: The README embeds promotional links and banners for sponsors (Latitude.so), a common monetization model for open-source projects.

Quick Start Guide

Since this is a documentation repository, getting started is extremely simple:

1. Clone the Repository:

   git clone https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git

2. Browse Content:
   • Open the README.md file directly to view the tool list.
   • Click on the folder of the tool you're interested in (e.g., cursor/) to view its internal files and prompt content.
   • Or browse directly on the GitHub web interface.

Strengths, Weaknesses, and Use Cases

Strengths:

• High Information Scarcity: The project publicly discloses a large amount of "internal" information from closed-source commercial tools, which is extremely valuable for developers wanting to understand the underlying logic of AI tools, conduct prompt engineering research, or perform competitive analysis.
• Centralized and Actively Updated Content: Aggregates scattered, unofficial information in one place and maintains a high update frequency, solving the problem of information fragmentation.
• Learning and Reverse Engineering Samples: Provides valuable learning and reverse analysis samples for AI security researchers, prompt hackers, and AI product developers.

Weaknesses:

• Legal and Ethical Risks: The project's core content involves potential violations of commercial product terms of service. Collecting and disseminating these "leaked" prompts carries legal and ethical controversies.
• Information Timeliness and Accuracy: AI tool prompts are frequently updated; the content in the repository may be outdated, and its 100% accuracy cannot be guaranteed (may originate from community speculation or unofficial sources).
• Non-Original Code/Tools: The project itself does not provide any original software or analysis tools; it is merely an information "conveyor."

Use Cases:

• AI Product Managers and Developers: Conduct competitive analysis to understand the design philosophy, constraint rules, and functional boundaries of mainstream AI tools.
• Prompt Engineers and Researchers: Study prompt design patterns from top AI applications, learning how to write efficient and safe system prompts.
• AI Security Practitioners: Analyze real-world cases of security risks like prompt injection and data leakage.
• AI Enthusiasts and Learners: Satisfy curiosity about the internal workings of AI black boxes and obtain learning materials.

Community and Popularity

• Stars (136,967): This is a phenomenal level of popularity, far exceeding similar Awesome list projects. This fully demonstrates the developer community's immense curiosity about the "internal secrets" of AI tools and their recognition of this resource's value.
• Topics: Accurately covers the most popular AI coding tools like cursor, devin, windsurf, copilot, with excellent SEO optimization.
• Discord Community: Has a dedicated Discord server (LeaksLab) for discussion and sharing updates, forming a subculture community centered around "AI leaks."
• Update Frequency: The README indicates the last update was in May 2026, showing the project is still actively maintained, continuously tracking new tools and updates.
• Star History: The Star History chart in the README shows explosive growth in a short period, typically resulting from viral social media spread or recommendations from KOLs.

Summary: This project has become a phenomenal open-source project due to its highly controversial value and precise timing (the AI tool boom). It is not a technical product but an information intelligence station. Its massive star count reflects the community's thirst for "inside knowledge." For target users, it is an invaluable treasure trove, but users should also be mindful of potential legal risks.

Technical Information

• 💻 Language: N/A
• 📂 Topics: ai, bolt, cluely, copilot, cursor
• 🕐 Updated: 2026-03-13
• 🔗 Visit GitHub Repository

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Data updated on 2026-05-09 · Stars count based on actual GitHub data