← Back to Leaderboard
Project comparison
Prompt Engineering vs System Prompts And Models Of Ai Tools
Compare adoption, momentum, maintenance health, and project basics before choosing which tool to evaluate deeper.
Prompt Engineering
22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.
7.5K
Stars
0
Weekly
39/100
Health
System Prompts And Models Of Ai Tools
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
137.2K
Stars
0
Weekly
42/100
Health
Quick Take
Adoption
System Prompts And Models Of Ai Tools has the larger GitHub footprint with 137.2K stars.
Momentum
Prompt Engineering is currently growing faster at 0 stars this week.
Maintenance
System Prompts And Models Of Ai Tools has the stronger health score at 42/100.
Side-by-side Metrics
| Signal | Prompt Engineering | System Prompts And Models Of Ai Tools |
|---|---|---|
| GitHub stars | 7.5K | 137.2K |
| Weekly growth | 0 | 0 |
| Health score | 39 | 42 |
| Contributors | 5 | 29 |
| Commits per week | 1.0 | 1.6 |
| Open issues | 3 | 140 |
| Language | Jupyter Notebook | N/A |
| License | NOASSERTION | GPL-3.0 |
| Last commit | 27d ago | 2d ago |
| Last release | N/A | N/A |
Weekly AI open-source movers
Get the fastest-growing projects, useful MCP servers, and technical reads in one weekly email.