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 alhinawi · Codex Skill · ★ 81
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is telegram-notifier safe to install? View the security audit →
telegram-notifier Skills • AI Agents • Two-Way Control Bridge • Remote Dev Universal Telegram notification & interactive control bridge for AI coding agents: real-time alerts on your phone whenever tasks finish, human approvals with interactive buttons, plus two-way control to execute prompts, switch workspaces, and stop tasks directly from your smartphone! Quick Start Install and set up the skill across all your AI coding agents (Cursor, Claude Code, Antigravity, Windsurf) in one command: The interactive setup wizard will run automatically to: Connect your Telegram Bot Token and auto-detect your Chat ID. Configure workspace folders for scanning recent projects (WORKSPACEDIR
| Stars | 81 |
| Forks | 0 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 66.9664419126625/100 |
| Last Updated | 2026-09-13 |
| Created | 2026-08-24 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~11k |
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telegram-notifier is Universal Telegram Notifier Plugin & Skill for AI Agents (Antigravity, Claude Code, Codex, Cursor, Windsurf) + Remote Control Setup. It is categorized as a Codex Skill with 81 GitHub stars.
telegram-notifier is primarily written in JavaScript.
You can find installation instructions and usage details in the telegram-notifier GitHub repository at github.com/alhinawi/telegram-notifier. The project has 81 stars and 0 forks, indicating an active community.
telegram-notifier is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to telegram-notifier on Agent Skills Hub include theorist. 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: