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 littlebearapps · Codex Skill · ★ 62
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is untether safe to install? View the security audit →
Telegram bridge for AI coding agents. Send tasks by voice or text, stream progress live, and approve changes — from your phone, anywhere. Works with Claude Code · Codex · OpenCode · Pi · Gemini CLI · Amp <p align="center
| Stars | 62 |
| Forks | 8 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 62.4016597234485/100 |
| Open Issues | 161 |
| Last Updated | 2026-08-03 |
| Created | 2026-02-07 |
| Platforms | claude-code, cli, codex, gemini, python |
| Est. Tokens | ~19k |
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untether is Code from anywhere — Telegram bridge for AI coding agents (Claude Code, Codex, OpenCode, Pi, Gemini CLI, Amp). Stream progress, approve actions, and send tasks by voice from your phone.. It is categorized as a Codex Skill with 62 GitHub stars.
untether is primarily written in Python. It covers topics such as ai-agents, claude-code, cli.
You can find installation instructions and usage details in the untether GitHub repository at github.com/littlebearapps/untether. The project has 62 stars and 8 forks, indicating an active community.
untether is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to untether on Agent Skills Hub include vibepod-cli, sage, bit-office. 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: