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 iniwap · Agent Tool · ★ 59
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is AIForge safe to install? View the security audit →
🚀 AIForge - 智能意图自适应执行引擎 将自然语言指令转化为可执行代码的AI驱动自动化引擎 🚀 快速开始 • 🧠 核心功能 • ⚡ 联系支持 • 🌐 应用场景 🎯 什么是 AIForge？ 🚧 项目状态: 目前处于全力开发阶段，版本更新比较频繁，敬请关注。 AIForge 是一个智能执行引擎，它消除了自然语言指令与代码执行之间的壁垒。通过先进的指令分析和自适应执行架构，AIForge 提供： 🧠 深度理解：多维度指令解析，精准捕获意图
| Stars | 59 |
| Forks | 24 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 59.630027630397/100 |
| Open Issues | 2 |
| Last Updated | 2025-09-10 |
| Created | 2025-07-16 |
| Platforms | cli, python |
| Est. Tokens | ~213k |
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AIForge is 🚀 智能意图自适应执行引擎，只需一句话，让AI帮你搞定想做的事（数据分析与处理、高时效性内容创作、最新信息获取、数据可视化、系统交互、自动化工作流、代码开发等). It is categorized as a Agent Tool with 59 GitHub stars.
AIForge is primarily written in Python. It covers topics such as agent, agent-zero, agent0.
You can find installation instructions and usage details in the AIForge GitHub repository at github.com/iniwap/AIForge. The project has 59 stars and 24 forks, indicating an active community.
AIForge is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to AIForge on Agent Skills Hub include ai-agent-tools-catalog, decipher-research-agent, eval-view. 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: