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 xjli360 · Codex Skill · ★ 119
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is sealeap-amazon-skills safe to install? View the security audit →
SeaLeap Amazon Skills 搜罗全宇宙关于亚马逊电商的知识，让每一份好经验成为可复用的 Skill。 从官方课程到社媒公开分享，从选品、Listing 到广告、库存与经营，把知识整理成能交给 AI Agent 使用的工作流。 项目目标 · 技能目录 · 开始使用 · 免费开源承诺 · 参与贡献 项目目标 搜罗全宇宙关于亚马逊电商的知识。 SeaLeap 希望把分散在不同平台、不同形式里的实用经验，整理成一个持续生长的亚马逊电商知识库和 Agent Skill 库。 收录与整理的范围包括： 亚马逊官方授权内容：在授权范围内整理官方课程、培训材料与行业资料。 亚马逊官方公众号内容：提炼公开发布的运营指南、产品解读、案例与行业洞察。 抖音、微信、小红书、B 站、YouTube 等社媒公开内容：提炼亚马逊电商知识领袖公开分享中
| Stars | 119 |
| Forks | 15 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 66.3178185235771/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-15 |
| Created | 2026-08-21 |
| Platforms | codex, python |
| Est. Tokens | ~15k |
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sealeap-amazon-skills is Reusable Agent Skills for Amazon product research, listings, advertising, inventory, and operations.. It is categorized as a Codex Skill with 119 GitHub stars.
sealeap-amazon-skills is primarily written in Python. It covers topics such as advertising, agent-skills, ai-agents.
You can find installation instructions and usage details in the sealeap-amazon-skills GitHub repository at github.com/xjli360/sealeap-amazon-skills. The project has 119 stars and 15 forks, indicating an active community.
sealeap-amazon-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to sealeap-amazon-skills on Agent Skills Hub include fullstack-mkt-skills, email-marketing-bible, amazon-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: