by asukaminato0721 · AI Tool · ★ 202
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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.
| Stars | 202 |
| Forks | 29 |
| Language | TypeScript |
| Category | AI Tool |
| License | Apache-2.0 |
| Quality Score | 64/100 |
| Open Issues | 5 |
| Last Updated | 2026-10-08 |
| Created | 2024-11-17 |
| Platforms | gemini, node |
| Est. Tokens | ~9k |
telegram group summary bot Image by imagen-3 on ImageFX, prompt "an icon for telegram group message summarize and search message bot sketchy" Feel scared when seeing 2000+ unread in groups? Now you can read them by LLM! Use d1, cf worker, ai gateway, gemini-2.5-flash. NOTICE Due to current usage exceeded maximum DB size 500M , please deploy your own bot. And you can keep a much longer log.
Looking for a telegram-summary-bot alternative? If you're comparing telegram-summary-bot with other ai tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
MCP Server for Telegram
Anthropic Claude & Google Bard Bot for Telegram.
构建受监督的、自我进化的 Agent 组织的基础设施 | Infrastructure for supervised, self-improving agent organization. 飞书/Telegram 手机端
A curated list of OpenClaw resources, tools, skills, tutorials & articles. OpenClaw (formerly Moltbot / Clawdb
State of the Art 82% OSWorld Computer Using Agent, production-ready. Remote and Local! Setup using one API Key
OpenClaw 中文文档站 | AI 智能体框架 源码剖析 安装教程 | WhatsApp Telegram Discord 飞书 多通道机器人
Explore other popular ai tool tools:
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: