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 microxxx · Agent Tool · ★ 139
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-langchain-zh safe to install? View the security audit →
awesome-langchain-zh awesome-langchain 中文版 🔥🔥🔥 企业级llm工具Llmware🔥🔥🔥 目录 awesome-langchain-zh 目录 LangChain框架 其他语言移植版本 工具 低代码 服务 代理 模板 平台 开源项目 知识管理 其他聊天机器人 学习 笔记本 视频 文章 其他LLM框架 补充 不维护 LangChain框架 LangChain : 原始的🐍 LangChain.js : js版本的兄弟✨ langgraph : 基于langchain 的 rag或agent框架 概念: Langchain概念文档 Twitter账户: 关注以获取最新更新 Youtube频道 Discord: 讨论 Langchain博客: 官方Langchain博客 LangChainHub : 收
| Stars | 139 |
| Forks | 14 |
| Category | Agent Tool |
| License | CC0-1.0 |
| Quality Score | 53.789323343007/100 |
| Open Issues | 1 |
| Last Updated | 2024-05-26 |
| Created | 2023-06-25 |
| Est. Tokens | ~18k |
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awesome-langchain-zh is langchain 工具,流程设计组件,服务,代理以及相关学习文档的合集(agent,service,tutorials,flow-design). It is categorized as a Agent Tool with 139 GitHub stars.
You can find installation instructions and usage details in the awesome-langchain-zh GitHub repository at github.com/microxxx/awesome-langchain-zh. The project has 139 stars and 14 forks, indicating an active community.
awesome-langchain-zh is released under the CC0-1.0 license, making it free to use and modify according to the license terms.
The top alternatives to awesome-langchain-zh on Agent Skills Hub include palico-ai, bedrock-kb-rag-workshop, mcp-client-cli. 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: