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 SenteLabsAI · Agent Tool · ★ 4.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is OpenExecutive safe to install? View the security audit →
Open Executive An AI system that acts as your company's virtual executive team — a senior advisor with Harvard MBA-level knowledge, customized for your specific business. Demo A walkthrough of Open Executive in action — watch on YouTube. What It Does Developed by sentelabs.ai Open Executive provides a single coherent executive voice backed by eight specialist AI agents: Chief Strategy Officer — competitive analysis, M&A, market positioning, OKRs Chief Financial Officer — financial modeling, fundraising, unit economics, cash flow Chief HR/People Officer — hiring, compensation, performance, culture General Counsel — contracts, IP, employment law basics, compliance Chief Operating Officer — process design, vendor management, operational scaling Chief Marketing Officer — GTM strategy, brand, communications, PR Chief
| Stars | 4,167 |
| Forks | 435 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 68.1370362126514/100 |
| Open Issues | 5 |
| Last Updated | 2026-09-13 |
| Created | 2026-06-11 |
| Platforms | claude-code, python |
| Est. Tokens | ~18k |
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OpenExecutive is AI-powered virtual executive team — a single coherent executive persona backed by 8 specialist agents (FastAPI + Next.js).. It is categorized as a Agent Tool with 4.2k GitHub stars.
OpenExecutive is primarily written in Python. It covers topics such as ai, anthropic, claude.
You can find installation instructions and usage details in the OpenExecutive GitHub repository at github.com/SenteLabsAI/OpenExecutive. The project has 4.2k stars and 435 forks, indicating an active community.
The top alternatives to OpenExecutive on Agent Skills Hub include honcho, fragments, kiro-gateway. 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: