Flagged: sudo usage. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by 23blocks-OS · Codex Skill · ★ 792
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
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AI Maestro I was running 35 AI agents across multiple terminals and became the human mailman between them. So I built AI Maestro. The OS for AI-first organizations — orchestrate any AI agent with persistent memory, agent-to-agent messaging, and multi-machine support. -lightgrey) Quick Start · Features · Documentation · Contributing The Story I gave an AI agent a real task — not autocomplete, a real engineering problem. It checked the code, read the logs, queried the database, and came back with the answer. That was the moment. This thing can actually work. Within a week I was running 35 agents across terminals. They were productive, but they couldn't talk to each other. I became the human message bus — copying context from one terminal, pasting into another. I was the b
| Stars | 792 |
| Forks | 108 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 66.7225958784134/100 |
| Open Issues | 10 |
| Last Updated | 2026-09-23 |
| Created | 2025-10-10 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~17k |
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Explore other popular codex skill tools:
ai-maestro is AI Agent Orchestrator with Skills System - Give AI Agents superpowers: memory search, code graph queries, agent-to-agent messaging. Manage Claude, Codex or any AI Agent from one dashboard. Move Agents. It is categorized as a Codex Skill with 792 GitHub stars.
ai-maestro is primarily written in TypeScript. It covers topics such as agent-communication, agent-skills, agentic-ai.
You can find installation instructions and usage details in the ai-maestro GitHub repository at github.com/23blocks-OS/ai-maestro. The project has 792 stars and 108 forks, indicating an active community.
ai-maestro is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ai-maestro on Agent Skills Hub include agent-skills, alook, amux. 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: