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 gobii-ai · Codex Skill · ★ 490
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is gobii-platform safe to install? View the security audit →
Gobii AI coworkers for teams with real work to do. This repository contains the open-source Gobii Platform for self-hosting and development. Looking for the hosted product? Start at Gobii AI coworkers. Official Website · Docs · Discord · Gobii Cloud Gobii is an AI coworker platform for running durable autonomous agents in production. The hosted Gobii product is available at gobii.ai; this repository contains the open-source platform for self-hosted deployments and development. Each agent can run continuously, wake from schedules and events, use real browsers, call external systems, and coordinate with other agents. Each agent can also be contacted like an AI coworker: assign it an identity, email or text it, and it keeps working
| Stars | 490 |
| Forks | 86 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 65.3049040117077/100 |
| Open Issues | 1 |
| Last Updated | 2026-08-21 |
| Created | 2025-08-30 |
| Platforms | docker, gemini, python |
| Est. Tokens | ~17k |
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gobii-platform is Your easy to use, always-on AI workforce 👾. It is categorized as a Codex Skill with 490 GitHub stars.
gobii-platform is primarily written in Python. It covers topics such as agentic-ai, ai, anthropic.
You can find installation instructions and usage details in the gobii-platform GitHub repository at github.com/gobii-ai/gobii-platform. The project has 490 stars and 86 forks, indicating an active community.
gobii-platform is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to gobii-platform on Agent Skills Hub include SimplerLLM, tools, samples. 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: