Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by AQBot-Desktop · Codex Skill · ★ 902
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is AQBot safe to install? View the security audit →
简体中文 العربية 运行截图
| Stars | 902 |
| Forks | 94 |
| Language | TypeScript |
| Category | Codex Skill |
| License | AGPL-3.0 |
| Quality Score | 63.6401815274292/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-15 |
| Created | 2026-03-24 |
| Platforms | cli, node |
| Est. Tokens | ~15k |
These tools work well together with AQBot for enhanced workflows:
Looking for a AQBot alternative? If you're comparing AQBot with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
Unified LLM gateway with weighted load balancing, observability & cost tracking. 统一的 LLM 网关,提供权重负载均衡、可观测性与费用追踪
Run your own organization of agents
Tactical AI Workspace Monitor & EDR
An app to monitor the (Codex) situation
🦞 OpenClaw & Hermes Agent 多引擎 AI 管理面板 — 内置 AI 助手(工具调用 + 图片识别 + 多模态),一键安装 | Tauri v2 跨平台桌面应用 | 11 种语言
📚 Sync skills across all AI CLI tools with one command and simplify team sharing. Supporting Codex, Claude Co
Explore other popular codex skill tools:
AQBot is ☁️ 轻量级高性能跨平台AI对话 + AI Agent + AI网关桌面客户端 | Lightweight, high-performance cross-platform AI dialogue + AI Agent + AI gateway desktop client. It is categorized as a Codex Skill with 902 GitHub stars.
AQBot is primarily written in TypeScript. It covers topics such as ai, ai-client, ai-desktop.
You can find installation instructions and usage details in the AQBot GitHub repository at github.com/AQBot-Desktop/AQBot. The project has 902 stars and 94 forks, indicating an active community.
AQBot is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to AQBot on Agent Skills Hub include llmio, huddol, kavach. 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: