sealeap-amazon-skills: Reusable Agent Skills for Amazon product research, listings, advertising, inventory, and operations

by xjli360 · Codex Skill · ★ 278

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install sealeap-amazon-skills

git clone https://github.com/xjli360/sealeap-amazon-skills.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 66/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

advertisingagent-skillsai-agentsamazon-adsamazon-sellercodexecommercemarketing-automation

Quick Facts

Stars278
Forks40
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score66/100
Open Issues1
Last Updated2026-10-16
Created2026-08-21
Platformscodex, python
Est. Tokens~15k

About sealeap-amazon-skills

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

Compatible Skills

These tools work well together with sealeap-amazon-skills for enhanced workflows:

  • amazon_ads_mcp — semantic(0.67)+complementary+rare_topics+same_lang+similar_pop+shared_platform (78%)
  • ZooData-Skills — semantic(0.55)+complementary+rare_topics+same_lang+similar_pop+shared_platform (74%)
  • amazon-listing-doctor — semantic(0.55)+complementary+rare_topics+same_lang+similar_pop+shared_platform (74%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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