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 josstei · Codex Skill · ★ 462
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is maestro-orchestrate safe to install? View the security audit →
Maestro Multi-agent development orchestration platform — 22 specialists, 4-phase orchestration, native parallel subagents, persistent sessions, and standalone review/debug/security/perf/seo/a11y/compliance commands. Runs on both Gemini CLI and Claude Code. Table of Contents Overview Features Getting Started Prerequisites Installation Quick Start Commands Orchestration Standalone Tools Session Management Configuration Environment Variables Hooks Architecture Orchestration Flow Component Model Workflow Phases Agents Agent Roster Tool Access Philosophy Skills Parallel Execution
| Stars | 462 |
| Forks | 35 |
| Language | JavaScript |
| Category | Codex Skill |
| License | Apache-2.0 |
| Quality Score | 76.9226053069529/100 |
| Open Issues | 7 |
| Last Updated | 2026-08-07 |
| Created | 2026-02-09 |
| Platforms | claude-code, cli, codex, gemini, node |
| Est. Tokens | ~117k |
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maestro-orchestrate is Multi-agent orchestration platform for Gemini CLI, Claude Code, Codex, and Qwen Code — 39 specialists, parallel subagents, persistent sessions, and built-in code review, debugging, security, SEO, acce. It is categorized as a Codex Skill with 462 GitHub stars.
maestro-orchestrate is primarily written in JavaScript. It covers topics such as agentic, ai-agents, anthropic.
You can find installation instructions and usage details in the maestro-orchestrate GitHub repository at github.com/josstei/maestro-orchestrate. The project has 462 stars and 35 forks, indicating an active community.
maestro-orchestrate is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to maestro-orchestrate on Agent Skills Hub include quint-code, claude-code-workflows, awesome-llm-skills. 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: