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

Analysis updated 2026-05-18

★ 136,812Audience · researcherComplexity · 1/5LicenseSetup · easy

Mindmap

mindmap
  root((repo))
    What it is
      System prompts
      AI tool internals
      Extracted models
    Tools included
      Cursor
      Claude Code
      Perplexity
      Replit
    Use cases
      Understand AI behavior
      Learn prompt design
      Security research
    Audience
      AI researchers
      Developers
      Security teams

mindmap root((repo)) What it is System prompts AI tool internals Extracted models Tools included Cursor Claude Code Perplexity Replit Use cases Understand AI behavior Learn prompt design Security research Audience AI researchers Developers Security teams

Click or tap to explore — scroll the page freely

What do people build with it?

USE CASE 1

Study how popular AI coding assistants are prompted and configured internally.

USE CASE 2

Learn prompt engineering techniques by examining real-world examples from production AI tools.

USE CASE 3

Research security implications of exposed system prompts in AI products.

How does it compare?

	x1xhlol/system-prompts-and-models-of-ai-tools	langchain-ai/langchain	open-webui/open-webui
Stars	136,812	135,947	135,781
Language	—	Python	Python
Setup difficulty	easy	moderate	hard
Complexity	1/5	3/5	4/5
Audience	researcher	developer	developer

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

Use it freely, but any project you distribute that includes this code must also be GPL-licensed and open source.

In plain English

Based on the description and topics, this repository is a collection of system prompts, internal tools, and AI models extracted from a long list of named AI products. The description lists 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, plus other open-sourced ones. The topics list adds bolt, cluely, copilot, cursor, cursorai, devin, and github-copilot. The README itself does not describe the contents in any structural way, it consists mainly of sponsor banners, support links, a security notice for AI startups about exposed prompts being attacked, contact information, and a star-history badge. As a result, the README does not provide further detail about how the prompts are organized, where they came from, what format they use, or how someone is meant to consume them. A complete explanation of the repository's structure and intended use is not possible from the provided data alone.

Copy-paste prompts

Prompt 1

Show me the system prompts used by Cursor and Claude Code to understand how they instruct AI models.

Prompt 2

What prompt patterns do Perplexity and Replit use to generate code suggestions?

Prompt 3

Help me analyze the differences between system prompts across multiple AI coding tools.

Prompt 4

Extract and compare the internal instructions from Devin AI and Windsurf to see how they differ.

Frequently asked questions

What is system-prompts-and-models-of-ai-tools?

A collection of system prompts and internal models extracted from popular AI coding tools like Cursor, Claude, Perplexity, and Replit.

What license does system-prompts-and-models-of-ai-tools use?

Use it freely, but any project you distribute that includes this code must also be GPL-licensed and open source.

How hard is system-prompts-and-models-of-ai-tools to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is system-prompts-and-models-of-ai-tools for?

Mainly researcher.

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