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 DLYZZT · Agent Tool · ★ 220
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is pi-desktop safe to install? View the security audit →
Pi Agent Desktop 把 Pi Coding Agent 变成真正的桌面工作台。 本地优先 · 零内部服务器 · 跨平台应用 English · 简体中文 下载 v0.2.3 · 截图 · 功能 · 快速开始 · 架构 · 变更记录 · 路线图 应用截图 技能浏览、启用与内容编辑 系统工具发现与托管运行时管理 核心能力 一个完整的 Agent 工作台 创建、切换、重命名和删除会话，并持续展示流式回复 新会话可根据首条有效消息在后台自动生成简短标题；可在设置中关闭，手动名称始终优先
| Stars | 220 |
| Forks | 24 |
| Language | TypeScript |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 66.1344221848952/100 |
| Open Issues | 8 |
| Last Updated | 2026-09-19 |
| Created | 2026-07-12 |
| Platforms | browser, node |
| Est. Tokens | ~16k |
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pi-desktop is A local-first, cross-platform Electron desktop workspace for Pi Coding Agent, with sessions, project files, browser tools, skills, plugins, and messaging integrations.. It is categorized as a Agent Tool with 220 GitHub stars.
pi-desktop is primarily written in TypeScript. It covers topics such as agentic-ai, ai-agent, ai-coding-assistant.
You can find installation instructions and usage details in the pi-desktop GitHub repository at github.com/DLYZZT/pi-desktop. The project has 220 stars and 24 forks, indicating an active community.
pi-desktop is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to pi-desktop on Agent Skills Hub include palot, openclaw-desktop, project-raven. 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: