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 fitlab-ai · Codex Skill · ★ 84
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agent-infra safe to install? View the security audit →
Agent Infra Collaboration infrastructure for AI coding agents — skills, workflows, and sandboxes for Claude Code, Codex, Gemini CLI, and OpenCode. From issue to merged PR in 11 commands. Define a requirement, let AI handle analysis, planning, coding, and three-stage review — you only step in when it matters. = 22"
| Stars | 84 |
| Forks | 5 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 71.1181576177074/100 |
| Open Issues | 25 |
| Last Updated | 2026-09-20 |
| Created | 2026-03-06 |
| Platforms | claude-code, cli, codex, gemini, node |
| Est. Tokens | ~25k |
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agent-infra is Collaboration infrastructure for AI coding agents | AI 编程代理的协作基础设施. It is categorized as a Codex Skill with 84 GitHub stars.
agent-infra is primarily written in TypeScript. It covers topics such as ai, ai-collaboration, claude-code.
You can find installation instructions and usage details in the agent-infra GitHub repository at github.com/fitlab-ai/agent-infra. The project has 84 stars and 5 forks, indicating an active community.
agent-infra is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to agent-infra on Agent Skills Hub include claude-code-open, sudocode, deepcontext-mcp. 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: