Article-Assistant--RAG-Telegram-Bot: A sophisticated RAG Telegram bot that transforms articles and documents into interactive knowledge bases

by KonstantinVanov · Agent Tool · ★ 55

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install Article-Assistant--RAG-Telegram-Bot

git clone https://github.com/Konstantin-vanov-hub/Article-Assistant--RAG-Telegram-Bot.git
git clone https://github.com/Konstantin-vanov-hub/Article-Assistant--RAG-Telegram-Bot

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 72/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentchatgptdockerlangchainllma-indexopenaipythonpython-telegrambot-botrag-architecturesource-citations

Quick Facts

Stars55
Forks6
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score72/100
Last Updated2025-10-06
Created2025-08-03
Platformsdocker, python
Est. Tokens~14k

About Article-Assistant--RAG-Telegram-Bot

Article Assistant (RAG Telegram Bot) Contact: @Konstantinvanov A Telegram bot for Q&A about articles using Retrieval-Augmented Generation. Indexes web content and PDF files, then provides accurate answers with sources.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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