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 Lianues · Agent Tool · ★ 149
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Lim-Code safe to install? View the security audit →
LimCode 一个强大的 VS Code AI 编程助手 支持多渠道 AI 模型 MCP 🔄 近期更新重点 工具说明强化正则触发清单：、、、、字符类、分组和锚点都必须显式设置 。 非正则零命中时新增 诊断，提示模型 query 看起来像正则但当前按字面量搜索，并给出 重试建议。 保留 的严格字面量语义，不自动把 Markdown 表格、TypeScript union 或 Shell 管道里的 当正则 OR。 完整发布记录见 CHANGELOG.md。 ✨ 特性 🤖 多渠道支持 Gemini - 原生支持 Google Gemini API，包括 Function Calling OpenAI - 兼容 OpenAI 格式的 API（ChatGPT、Azure OpenAI 等） Anthropic - 支持 Claude 系列模型 自定义格式 - XML 工具调用格式，适用于更多模型 🛠️ 智能工具系统 内置丰富的工具，让 AI 能够直接操作您的代码：
| Stars | 149 |
| Forks | 23 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65.4666873005506/100 |
| Open Issues | 17 |
| Last Updated | 2026-05-31 |
| Created | 2025-12-18 |
| Platforms | node, vscode |
| Est. Tokens | ~506k |
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Lim-Code is 一个强大的 VS Code AI 编程助手. It is categorized as a Agent Tool with 149 GitHub stars.
Lim-Code is primarily written in TypeScript. It covers topics such as ai, ai-agents, ai-assistant.
You can find installation instructions and usage details in the Lim-Code GitHub repository at github.com/Lianues/Lim-Code. The project has 149 stars and 23 forks, indicating an active community.
Lim-Code is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Lim-Code on Agent Skills Hub include agnix, argus, calva-backseat-driver. 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: