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 sruthir28 · AI Skill · ★ 134
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is enterprise-ai-skills safe to install? View the security audit →
Enterprise AI Skills AI-powered consulting frameworks and PM tools. Built by a former McKinsey consultant, now shipping AI workflows that actually work. Who this is for: PMs, consultants, strategists, and ops leaders who want to apply proven frameworks instantly — not write prompts from scratch. Skills Frameworks Agents 4-age
| Stars | 134 |
| Forks | 25 |
| Language | Python |
| Category | AI Skill |
| License | MIT |
| Quality Score | 62.5155582118583/100 |
| Last Updated | 2026-09-01 |
| Created | 2025-11-25 |
| Platforms | claude-code, python |
| Est. Tokens | ~14k |
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enterprise-ai-skills is Open-source AI skills for enterprise professionals. McKinsey consulting frameworks, PM workflows, and practical tools. Currently for Claude, expanding to other LLMs.. It is categorized as a AI Skill with 134 GitHub stars.
enterprise-ai-skills is primarily written in Python. It covers topics such as ai, claude, consulting.
You can find installation instructions and usage details in the enterprise-ai-skills GitHub repository at github.com/sruthir28/enterprise-ai-skills. The project has 134 stars and 25 forks, indicating an active community.
enterprise-ai-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to enterprise-ai-skills on Agent Skills Hub include awesome-claude-skills, pm-claude-code-setup, Claude-Skill-Potions. 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: