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 Gingiris-1031 · Claude Skill · ★ 81
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is gingiris-skills safe to install? View the security audit →
Gingiris Skills — AI Growth & Operations Toolkit Reusable Claude Code skills for AI startup operators. Open source, MIT licensed. 4-language support: 🇺🇸 EN · 🇨🇳 ZH · 🇯🇵 JA · 🇰🇷 KR ⚡ Install All 55+ Skills in One Command Or install a single skill: Browse all skills: gingiris.tools/skills · clawhub.ai/user/gingiris Skills Index Core Growth Playbooks () [↗](https://clawhub.a
| Stars | 81 |
| Forks | 5 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 64.4169688219478/100 |
| Last Updated | 2026-09-20 |
| Created | 2026-05-25 |
| Platforms | claude-code, python |
| Est. Tokens | ~14k |
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gingiris-skills is Reusable Claude Code skills for AI startup operators. Open source, MIT licensed.. It is categorized as a Claude Skill with 81 GitHub stars.
gingiris-skills is primarily written in Python. It covers topics such as ai-agent, ai-startup, claude-code.
You can find installation instructions and usage details in the gingiris-skills GitHub repository at github.com/Gingiris-1031/gingiris-skills. The project has 81 stars and 5 forks, indicating an active community.
gingiris-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to gingiris-skills on Agent Skills Hub include socialclaw, creative-director-skill, ai-marketing-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: