by LtdEdition-Peng · Agent Tool · ★ 73
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.
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 | 73 |
| Forks | 18 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 56/100 |
| Last Updated | 2025-08-17 |
| Created | 2025-07-30 |
| Platforms | python |
| Est. Tokens | ~2k |
English Version English README Python ReAct Agent 自动化助手 项目简介 这是一个基于 ReAct（Reasoning and Acting）模式的智能代理系统，该系统结合了推理和行动能力，能够通过多种工具与环境交互，同时结合CodeAct自动完成复杂任务。 使用Langchain 框架快速实现 LtdEdition-Peng/LangchainAutoAgent(GitHub) 核心特性 🤖 智能推理: 基于 Google Gemini 模型的智能对话和推理能力 🔧 多工具集成: 支持文件操作、网页搜索、系统命令执行等多种工具 💬 对话管理: 智能的上下文管理和对话状态维护 🔄 自动循环: 支持多步推理和工具调用的自动化流程 ⚙️ 灵活配置: 可配置的参数和环境设置 系统架构 核心组件 工作流程 用户输入 → 接收用户问题...
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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: