by runtm-ai · Agent Tool · ★ 300
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🔒 Is runtm safe to install? View the security audit →
Runtm Open-source sandboxes where coding agents build and deploy. Spin up isolated environments where Claude Code, Cursor, Codex, and other agents code and ship software. With live URLs, logs, and previews. Website · Docs · Get Started Demo https://github.com/user-attachments/assets/8d6d5ab8-a5c4-4a3d-8ef1-5d20b67ed3ee Why Runtm? Sandboxes for yolo agents – Let agents code with full permissions in isolated environments. No risk to your machine or cloud. Run any coding agent – Claude Code, Cursor, Codex, Gemini CLI, and more. Bring your favorite. Real URLs instantly – Agents deploy to live HTTPS endpoints. Test, share, and iterate. Logs and observability – See what your agent built, debug issues, fix and redeploy. Quick Start bash Install uv tool install runtm Start a local sandbox session runtm session start Your agent builds inside the sandbox... Dep
uv tool install runtm
pipx install runtmTaken from the project's README on GitHub. Check the security audit before running it.
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 →
| Stars | 300 |
| Forks | 40 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 71.021285859871/100 |
| Open Issues | 29 |
| Last Updated | 2026-10-12 |
| Created | 2026-01-02 |
| Platforms | claude-code, python |
| Est. Tokens | ~15k |
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runtm is Open-source sandboxes where coding agents build and deploy. Spin up isolated environments where Claude Code, Cursor, and other agents code and deploy software.. It is categorized as a Agent Tool with 300 GitHub stars.
runtm is primarily written in Python. It covers topics such as agent-runtime, agentic, ai-agents.
The README on GitHub (github.com/runtm-ai/runtm) gives: uv tool install runtm , then pipx install runtm. Usage details are in the same README.
The top alternatives to runtm on Agent Skills Hub include platform, argus, code-on-incus. 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: