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 jtgsystems · Agent Tool · ★ 181
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Custom-Modes-Roo-Code safe to install? View the security audit →
Custom Modes for Roo Code 🤖 ⭐ Star this repo if you find it useful! ⭐ Professional AI Agent Configuration Library for Roo Code — 2026 Edition A comprehensive collection of 225 specialized AI agents designed for modern software development, following 2026 security-first principles and best practices. Includes 11 SOTA reasoning personas for advanced cognitive workflows. 🚀 Quick Start 📚 Table of Contents Overview [Agent Categories
| Stars | 181 |
| Forks | 30 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 71.1634442178188/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-02 |
| Created | 2025-02-05 |
| Platforms | browser, claude-code, docker, k8s, python, vscode |
| Est. Tokens | ~808k |
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Custom-Modes-Roo-Code is 🚀 Custom modes for Roo Code VS Code extension - Enhanced AI coding assistance configurations. It is categorized as a Agent Tool with 181 GitHub stars.
Custom-Modes-Roo-Code is primarily written in Python. It covers topics such as agents, ai, automation.
You can find installation instructions and usage details in the Custom-Modes-Roo-Code GitHub repository at github.com/jtgsystems/Custom-Modes-Roo-Code. The project has 181 stars and 30 forks, indicating an active community.
Custom-Modes-Roo-Code is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Custom-Modes-Roo-Code on Agent Skills Hub include orchestkit, claudex, ai-agent-tools-catalog. 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: