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 KrishMunot · Agent Tool · ★ 2.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-startup safe to install? View the security audit →
Awesome Startup A curated list of awesome books, videos, courses, tools and resources about making a startup. The timeless advice on this list still holds: talk to users, ship fast, watch your runway. What changed is the cost of building. A founder in 2026 can put a working product in front of customers before a 2015 founder would have finished hiring, so the sections below cover both the fundamentals and the AI-era tooling that compresses the loop. Contents Books Videos and Courses Essays and Reading AI for Founders Engineering and Infrastructure Product and Analytics Design and Brand Incorporation, Legal and Equity Finance and Banking Security and Compliance Venture Capital and Raising Money Accelerators Marketing, Sales and Metrics Marketing Tools
| Stars | 2,333 |
| Forks | 272 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 54.1336412956151/100 |
| Last Updated | 2026-08-26 |
| Created | 2015-12-16 |
| Est. Tokens | ~13k |
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awesome-startup is :sunglasses: All the required resources to build your own startup. It is categorized as a Agent Tool with 2.3k GitHub stars.
You can find installation instructions and usage details in the awesome-startup GitHub repository at github.com/KrishMunot/awesome-startup. The project has 2.3k stars and 272 forks, indicating an active community.
awesome-startup is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to awesome-startup on Agent Skills Hub include awesome-web-agents, awesome-ai-sdks, awesome-agent-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: