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 7-e1even · Codex Skill · ★ 277
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is learn-agent safe to install? View the security audit →
learn-agent · 从零写一个能活下来的 AI Agent 简体中文 · English 快速跳转 · 适合谁读 · 30 秒跑起来 · 15 篇目录 · 完整实现 Reina · 给个 Star 一个 循环是 agent 的全部秘密——但只够它活 5 分钟。 剩下的部分——让它在真实任务里活过 5 小时——就是这 15 篇笔记记的东西。 想搞懂 Claude Code、Codex、opencode 这类 coding agent 内部到底怎么实现？这个仓库是我从 0 开发自己的 agent 时的踩坑笔记：15 篇渐进式笔记 + 15 份零依赖、单文件、直接能跑的代码，每篇解决一个真实翻车现场。 [!IMPORTANT] 和别的"手写 agent"教程不一样的地方：这里的机制不是照着 API 文档想象的，而是从一个真实在跑、完整开源的桌面 coding agent 产品——Reina——简化移植而来，每一条报错、每一个机制优化，都是线上踩过的坑。 学完这 15 篇想看生产级完整源码，直接去 👉 Reina-Agent/Reina 这份笔记适合你吗 对着下面三条自查，中一条就值得读： 你照教程写过 agent demo，但一上真实任务就失控：空转烧钱、上下文爆窗、跑半小时忘了最初任务； 你每天在用 Claude Code，想知道压缩、缓存、子代理、权限审批这些"魔法"内部到底怎么做的；
| Stars | 277 |
| Forks | 16 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 59.0653104327017/100 |
| Last Updated | 2026-09-05 |
| Created | 2026-07-03 |
| Platforms | claude-code, cli, codex, gemini, node |
| Est. Tokens | ~14k |
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learn-agent is 学习Agent开发的笔记，尝试让Agent从可用到可靠. It is categorized as a Codex Skill with 277 GitHub stars.
learn-agent is primarily written in JavaScript. It covers topics such as agent, agent-harness, agent-loop.
You can find installation instructions and usage details in the learn-agent GitHub repository at github.com/7-e1even/learn-agent. The project has 277 stars and 16 forks, indicating an active community.
learn-agent is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to learn-agent on Agent Skills Hub include clawmetry, golembot, holysheep-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: