system-prompts-and-models-of-ai-tools
x1xhlol/system-prompts-and-models-of-ai-tools
A repository collecting system prompts and model info for popular AI tools like Cursor and Devin, helping developers optimize their AI usage.
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 Summary
What This Project Does
Simply put, this is a "prompt dictionary" collecting system instructions and model configs for popular AI coding tools like Cursor, Copilot, and Devin.
What Problems It Solves
You often can't control how AI tools respond. This provides reference solutions to understand why AI answers certain ways or how to tune instructions for better results, replacing blind trial and error.
Who It's For
1. Programmers using AI for coding
2. Prompt engineering enthusiasts
3. People curious about AI tool logic
Typical Use Cases
1. Learn how companies design AI instructions
2. Optimize performance of locally deployed open models
3. Compare response logic across different tools
Key Strengths & Highlights
Very comprehensive, covering mainstream tools from Cursor to Devin, frequent updates, and you can see the industry "standard answers" directly.
Getting Started Requirements
No coding skills needed, no deployment required. Just open the repo and read the text files. Zero cost to learn.
Purpose
Good for learning prompt writing or researching AI logic, but not recommended for direct commercial production use as some data may involve security risks or be outdated.
Category
Tech Stack
Project Info
- Primary Language
- â
- Default Branch
- main
- License
- GPL-3.0
- Homepage
- â
- Created
- Mar 5, 2025
- Last Commit
- yesterday
- Last Push
- yesterday
- Indexed
- Apr 19, 2026