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 ashish200729 · Agent Tool · ★ 52
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is orbiteditor safe to install? View the security audit →
Orbit Editor An open-source AI-powered code editor. Like Cursor. Any provider you want. https://github.com/user-attachments/assets/01c51dec-f037-43d9-b68b-2e3bdc582270 Website · Download · Features · Docs · Discord Orbit Editor is an open-source AI code editor forked from Void Editor and VS Code. Run AI agents on your codebase, checkpoint and visualize changes, and bring any model or host locally — messages go directly to providers without retaining your data. This repo contains the full source code for Orbit Editor's desktop app. If you're
| Stars | 52 |
| Forks | 11 |
| Language | TypeScript |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 52.2156973113354/100 |
| Open Issues | 6 |
| Last Updated | 2026-08-13 |
| Created | 2026-01-29 |
| Platforms | node, vscode |
| Est. Tokens | ~13k |
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orbiteditor is Open-source AI code editor and Cursor alternative with multi-agent workflows, BYOK, local models, and self-hosted agents for macOS and Windows.. It is categorized as a Agent Tool with 52 GitHub stars.
orbiteditor is primarily written in TypeScript. It covers topics such as anthropic, antigravity-ide, copilot.
You can find installation instructions and usage details in the orbiteditor GitHub repository at github.com/ashish200729/orbiteditor. The project has 52 stars and 11 forks, indicating an active community.
orbiteditor is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to orbiteditor on Agent Skills Hub include mkeditor, azure-agentic-infraops, github-copilot-api-vscode. 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: