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 autopus-ai · Codex Skill · ★ 111
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is autopus-adk safe to install? View the security audit →
🐙 Autopus-ADK A harness of the agents, by the agents, for the agents. Make your AI coding tools (Claude Code, Codex, Antigravity CLI, OpenCode, Oh My Pi) work like a real engineering team — with planning, testing, code review, and security audits built in. 16 agents. 53 skills in the library, a compact default catalog. One config across platforms. Paste this command into your AI coding agent's chat (Claude Code, Codex, OpenCode, etc.) — the agent will run it and set up everything automatically. Or run it directly in your terminal. Why Autopus · [Core Workflow](
| Stars | 111 |
| Forks | 73 |
| Language | Go |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 62.763069618882/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-20 |
| Created | 2026-03-20 |
| Platforms | claude-code, cli, codex, gemini, go |
| Est. Tokens | ~27k |
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autopus-adk is Autopus-ADK is of the agents, by the agents. for the agents. Multi-model orchestration (consensus/pipeline/debate/fastest). Architecture-as-Code, Lore decision tracking, SPEC/EARS engine.. It is categorized as a Codex Skill with 111 GitHub stars.
autopus-adk is primarily written in Go. It covers topics such as agent-framework, agentic-ai, ai-agents.
You can find installation instructions and usage details in the autopus-adk GitHub repository at github.com/autopus-ai/autopus-adk. The project has 111 stars and 73 forks, indicating an active community.
autopus-adk is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to autopus-adk on Agent Skills Hub include agent-skills, sage, jat. 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: