No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by blazickjp · Agent Tool · ★ 52
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is GPT-CodeApp safe to install? View the security audit →
GPT-CodeKnot 🚀 Embark on a coding adventure with GPT-CodeApp, your new AI-powered coding companion! 🎉 This isn't just another Chat-GPT clone; it's your gateway to a smoother coding experience, packed with features you've always wished for. 📚 Table of Contents Installation and Setup Usage Contributing Tests License Questions Features 🛠️ Installation and Setup Setting up GPT-CodeApp is as easy as 1, 2, 3! Our application consists of a frontend and a backend, both of which need to be set up separately. Jump straight into action with these simple setup steps for both the frontend and backend. Let's get the engines running! Backend: The Brain 🧠 Enter the Backend Lair:
| Stars | 52 |
| Forks | 12 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 64.9232865238977/100 |
| Open Issues | 2 |
| Last Updated | 2024-05-07 |
| Created | 2023-06-28 |
| Platforms | claude-code, python |
| Est. Tokens | ~531k |
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GPT-CodeApp is This project is everything Chat-GPT should be for developers! An advanced AI-driven coding companion tailored for developers. Seamlessly bridging the gap between traditional coding and AI capabilities. It is categorized as a Agent Tool with 52 GitHub stars.
GPT-CodeApp is primarily written in Python. It covers topics such as agents, ai, aider.
You can find installation instructions and usage details in the GPT-CodeApp GitHub repository at github.com/blazickjp/GPT-CodeApp. The project has 52 stars and 12 forks, indicating an active community.
GPT-CodeApp is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to GPT-CodeApp on Agent Skills Hub include repopack-py, manim-generator, ai-microcore. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: