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 buluslan · Claude Skill · ★ 77
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is amazon-listing-doctor safe to install? View the security audit →
🩺 Amazon Listing Doctor 根据亚马逊7月27日正式上线的标题新规，基于 CDQ / A9 / COSMO / Alexa 四大底座的亚马逊 Listing 全身体检 + 打分 Skill 想了解更多最新AI行业动态,AI+电商/广告的行业实践方法,人与AI如何协作共生的思考,请关注公众号:【新西楼.AI】 []() CDQ 质量分 · A9 收录 · COSMO 意图覆盖 · Alexa 可发现性 · 合规体检 · 标题词组分诊 Created By Buluu@新西楼 项目简介 Amazon Listing Doctor 是一款 Agent 原生 的亚马逊 Listing 质检 Skill,适配各类 AI Coding Agent。基于四大知识底座(CDQ / A9 / COSMO / Alexa for Shopping)对任意 Listing 做全身体检 + 打分,输出多维度健康报告。零依赖、零 API Key,纯标准库 Python,clone 下来就能跑。 只诊断不改写 —— 告诉你"哪里有问题、该改什么",改写由你自己决定。 兼容性:基于命令行调用,任何能执行 shell 的 Agent 都能用 —— 通过 Skill 加载 / AGENTS.md 注入 / 直接终端调用均可。 ✨ 它做什么 一条命令,给你的 Listing 出一份多维度体检报告: 我的 Listing 能
| Stars | 77 |
| Forks | 9 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 63.6866008932477/100 |
| Last Updated | 2026-09-17 |
| Created | 2026-07-28 |
| Platforms | claude-code, python |
| Est. Tokens | ~14k |
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amazon-listing-doctor is 亚马逊 Listing 质检+打分 Skill | Amazon listing health-check & scoring (CDQ/A9/COSMO/Alexa). It is categorized as a Claude Skill with 77 GitHub stars.
amazon-listing-doctor is primarily written in Python. It covers topics such as amazon, amazon-listing, amazon-seller.
You can find installation instructions and usage details in the amazon-listing-doctor GitHub repository at github.com/buluslan/amazon-listing-doctor. The project has 77 stars and 9 forks, indicating an active community.
amazon-listing-doctor is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to amazon-listing-doctor on Agent Skills Hub include awesome-amazon-ec-skills, amazon-skills, ZooData-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: