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 linghungegeg · Agent Tool · ★ 428
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Linghun safe to install? View the security audit →
Linghun 本地优先、证据优先的 AI 编程终端 把大模型接到真实项目、真实工具、真实权限、真实验证和真实上下文里。 English README · 中文白皮书 · English Whitepaper · 更新记录 · English Updates · App Bridge Linghun 可以理解成：给大模型装上一套工程化外骨骼。模型负责理解、推理和生成；Linghun 负责把模型接到真实项目、真实工具、真实权限、真实验证和真实上下文里。 普通聊天工具可以回答“应该怎么改”。Linghun 更关心另一件事：它有没有真的读过相关代码、有没有真的改对文件、有没有真的跑过验证、有没有把不确定的地方说清楚。 这就是 Linghun 反幻觉系统的价值：不是让模型少说错话那么简单，而是把“读事实、看证据、区分验证范围、拒绝空口完成、说明不确定性”变成运行时约束。模型仍然会推理和生成，但关键工程结论不能只靠模型自信。 Novita x Harbor 榜单记录 Linghun 已完成 Novita x Harbor Agent Benchmark 四个公开 TB2.1 榜单的运行与提交： [f77879ac-b30f-47bb-8fb1-650108364fc0](https://hub.harborframework.com/jobs/f77879
| Stars | 428 |
| Forks | 30 |
| Language | TypeScript |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 59.707279304499/100 |
| Last Updated | 2026-08-19 |
| Created | 2026-05-14 |
| Platforms | node |
| Est. Tokens | ~19k |
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Linghun is AGI-oriented, hallucination-resistant AI coding runtime grounded in evidence, tools, memory, agents, and verification.. It is categorized as a Agent Tool with 428 GitHub stars.
Linghun is primarily written in TypeScript. It covers topics such as agent-runtime, agi, ai.
You can find installation instructions and usage details in the Linghun GitHub repository at github.com/linghungegeg/Linghun. The project has 428 stars and 30 forks, indicating an active community.
Linghun is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to Linghun on Agent Skills Hub include open-multi-agent-kit, claude-code-open, Overture. 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: