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 tlgrcli · Agent Tool · ★ 187
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is tlgr safe to install? View the security audit →
tlgr Full Telegram account control from the terminal. Agent-friendly, daemon-based, with webhook event push. The command is ; the distribution on PyPI is , because the shorter name was taken by an unrelated project. is the recommendation because tlgr runs a long-lived daemon and wants its own environment; into a virtualenv works the same way. To track the development tip instead, install from the repository: For agents: logging in is a sequence of ordinary commands — then — so only reading the code needs a person. Secrets come from //, never argv. See AGENT.md for the full agent reference. is the same guida
| Stars | 187 |
| Forks | 3 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 61.3917680572813/100 |
| Open Issues | 5 |
| Last Updated | 2026-09-29 |
| Created | 2026-02-02 |
| Platforms | browser, cli, python |
| Est. Tokens | ~23k |
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tlgr is CLI for Telegram — agent-friendly, daemon-based, with webhook event push.. It is categorized as a Agent Tool with 187 GitHub stars.
tlgr is primarily written in Python. It covers topics such as agent-skills, ai-agents, automation.
You can find installation instructions and usage details in the tlgr GitHub repository at github.com/tlgrcli/tlgr. The project has 187 stars and 3 forks, indicating an active community.
tlgr is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to tlgr on Agent Skills Hub include ductor, roam-code, AutoRedTeam-Orchestrator. 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: