by jtgsystems · Agent Tool · ★ 185
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/jtgsystems/Custom-Modes-Roo-Code.gitTaken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 185 |
| Forks | 30 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 71/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-03 |
| Created | 2025-02-05 |
| Platforms | browser, claude-code, docker, k8s, python, vscode |
| Est. Tokens | ~808k |
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.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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: