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 0xfnzero · MCP Server · ★ 76
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is AI-Code-Tutorials safe to install? View the security audit →
🚀 AI Code Tutorials Claude Code 与 OpenAI Codex AI 辅助编程教程 从零基础到高级应用,系统学习 Claude Code、OpenAI Codex 和现代 AI 辅助编程工作流。 <p align="c
| Stars | 76 |
| Forks | 19 |
| Category | MCP Server |
| License | MIT |
| Quality Score | 65.2836437138134/100 |
| Last Updated | 2026-06-20 |
| Created | 2025-10-08 |
| Platforms | browser, claude-code, cli, codex, mcp |
| Est. Tokens | ~18k |
These tools work well together with AI-Code-Tutorials for enhanced workflows:
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AI-Code-Tutorials is Bilingual AI coding tutorials for Claude Code and OpenAI Codex: setup, CLI, Codex workflows, MCP, agents, code review, prompt engineering, and web projects.. It is categorized as a MCP Server with 76 GitHub stars.
You can find installation instructions and usage details in the AI-Code-Tutorials GitHub repository at github.com/0xfnzero/AI-Code-Tutorials. The project has 76 stars and 19 forks, indicating an active community.
AI-Code-Tutorials is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to AI-Code-Tutorials on Agent Skills Hub include agent-skills, awesome-ai-agent-skills, ask-user-questions-mcp. 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: