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 endorhq · Codex Skill · ★ 270
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is rover safe to install? View the security audit →
Rover Rover is a manager for AI coding agents that works with Claude Code, Codex, Cursor, Gemini, and Qwen. It helps you get more done, faster, by allowing multiple agents to work on your codebase simultaneously. The agents work in the background in separate, isolated environments: they don't interfere with your work or each other. Rover does not chang
| Stars | 270 |
| Forks | 32 |
| Language | TypeScript |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 72.3215802172934/100 |
| Open Issues | 42 |
| Last Updated | 2026-03-27 |
| Created | 2025-07-22 |
| Platforms | claude-code, codex, gemini, node |
| Est. Tokens | ~196k |
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rover is A manager for AI coding agents that works with Claude Code, Cursor, Gemini, Codex, and Qwen.. It is categorized as a Codex Skill with 270 GitHub stars.
rover is primarily written in TypeScript. It covers topics such as agentic-ai, ai, ai-agents.
You can find installation instructions and usage details in the rover GitHub repository at github.com/endorhq/rover. The project has 270 stars and 32 forks, indicating an active community.
rover is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to rover on Agent Skills Hub include llmio, tuui, codexia. 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: