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Agent Skill · 开发

amazon-return-optimizer(亚马逊退货优化器)

amazon-return-optimizer 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 OpenClaw 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

amazon-return-optimizer 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 6,403。

总安装 4,751周安装 202GitHub Stars 公开资料未说明下载 1,664核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:amazon-return-optimizer(亚马逊退货优化器)
来源仓库:https://github.com/mguozhen/amazon-return-optimizer
安装命令:
openclaw skills install amazon-return-optimizer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install amazon-return-optimizer

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

分析客户退货原因并提出减少退货率的解决方案。帮助识别列表准确性问题和包装改进建议。amazon-return-optimizer 属于开发类 Skill,可作为该场景下的辅助能力补充。基于实际退货数据生成针对性优化措施清单。

安装命令:openclaw skills install amazon-return-optimizer。需接入内部订单系统以获取完整退货记录进行分析。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install amazon-return-optimizer;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

amazon-return-optimizer 怎么安装?

在终端执行 openclaw skills install amazon-return-optimizer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

amazon-return-optimizer 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

amazon-return-optimizer 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

amazon-return-optimizer 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

amazon-return-optimizer 用的人多吗?

公开数据是累计安装 4,751 次,近一周安装 202 次,下载 1,664 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

amazon-return-optimizer 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

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6,636,960576只读MIT-0通过
entra-app-registration

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6,631,872764接触敏感数据未明确通过
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3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
amazon-return-optimizer

亚马逊退货优化器 · 本页

4,751—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
amazon-return-optimizer
description
Amazon return rate analyzer and reduction agent. Identify why customers return your products, fix listing accuracy issues, improve packaging to reduce damage returns, and manage FBA removal orders and reimbursement claims. Triggers: return rate, amazon returns, reduce returns, return analysis, fba returns, return reason, product return, amazon refund, return optimization, high return rate, listing accuracy, amazon removal order, fba reimbursement, return report, customer returns
allowed-tools
Bash
metadata
openclaw
homepage
https://github.com/mguozhen/amazon-return-optimizer

Amazon Return Rate Optimizer

High return rates kill your margins and can get your listing suppressed. Diagnose why customers return your product, fix the root causes, and recover lost revenue from FBA reimbursements.

Commands

return analyze [data]           # analyze return reasons and patterns
return audit [product]          # listing accuracy audit to reduce returns
return benchmark [category]     # return rate benchmarks for your category
return reimbursement            # FBA reimbursement claim guide
return packaging                # packaging improvement checklist
return response [reason]        # how to address specific return reason
return removal                  # FBA removal order strategy
return report                   # generate return reduction action plan

What Data to Provide

  • Return rate % — from Seller Central Voice of Customer or FBA Returns report
  • Return reasons — paste the return reason breakdown
  • Product category — for benchmark comparison
  • Current listing — title, bullets, images description
  • Packaging details — how product is packaged for shipment

Return Rate Benchmarks by Category

CategoryAverage Return RateHigh Alert
Electronics8–15%>20%
Clothing / Apparel20–40%>45%
Shoes25–35%>40%
Jewelry10–20%>25%
Toys5–10%>15%
Home & Kitchen5–12%>18%
Beauty / Health5–10%>15%
Sports & Outdoors5–10%>15%
Books1–3%>5%
Food & Grocery2–5%>8%

Amazon suppression risk: Return rate >15% above category average may trigger review

Return Reason Analysis Framework

Top Amazon Return Reasons & Fixes

Return ReasonRoot CauseFix
"Item defective or doesn't work"Manufacturing defectSupplier QC, materials upgrade
"Inaccurate website description"Listing mismatchRewrite bullets, update images
"Item smaller/larger than expected"Size not clearAdd size comparison image, dimensions in title
"Wrong item sent"Pick & pack errorWork with FBA, check SKU setup
"No longer needed"Impulse purchaseAdd urgency to listing, not fixable
"Item arrived damaged"Packaging failureImprove inner packaging, double-box
"Didn't like the quality"Expectation mismatchHonest listing, better photos
"Bought by mistake"Listing confusionClearer title, compatibility section
"Doesn't fit"Size guide missingAdd size chart, fit guide to listing
"Missing parts/accessories"Incomplete shipmentQC check on packing line

Prioritization Matrix

High Return Rate × Fixable = ACT NOW
High Return Rate × Not Fixable = Manage/Accept
Low Return Rate × Fixable = Nice to Have
Low Return Rate × Not Fixable = Ignore

Listing Accuracy Audit

Run this checklist to reduce expectation-gap returns:

Dimensions & Size

  • [ ] Exact dimensions in title or first bullet (not just in description)
  • [ ] Size comparison image (next to common object or hand)
  • [ ] Weight listed if relevant to customer decision
  • [ ] Package dimensions vs. product dimensions clearly distinguished

Materials & Quality

  • [ ] Material composition stated (100% cotton, not just "soft fabric")
  • [ ] Color accuracy: photo matches real product (calibrated display)
  • [ ] Texture/finish described accurately (glossy vs. matte, rough vs. smooth)
  • [ ] Fragrance/scent honestly described

Compatibility

  • [ ] Compatible models/sizes explicitly listed (for accessories)
  • [ ] Incompatible items listed ("Does NOT fit iPhone 15 Pro Max")
  • [ ] Power requirements, voltage, plug type (for electronics)
  • [ ] Age appropriateness (for toys, children's products)

What's in the Box

  • [ ] Complete list of included items in listing
  • [ ] What's NOT included (batteries, tools, etc.)
  • [ ] Flat lay image showing all components

Packaging Improvement Guide

Transit Damage Prevention

IssueSolution
Product shifting in boxAdd void fill (air pillows, paper)
Box crushingDouble-wall corrugated, minimum 32 ECT
Glass/fragile itemsBubble wrap + foam inserts, "Fragile" label
ElectronicsAnti-static bag + foam surround
Liquid productsSealed inner bag + absorbent pad

Amazon Drop Test Standard: Box should survive 3-foot drop on each face, edge, and corner

FBA Packaging Requirements

  • Products must be in sealed poly bag or box (no exposed products)
  • Barcodes scannable through packaging
  • Sets/bundles bagged together with "Sold as Set" label
  • Adult products in opaque packaging

FBA Reimbursement Claims

Amazon owes you money when:

  • Units lost in FBA warehouse
  • Units damaged by Amazon (not customer)
  • Customer returned item but Amazon didn't restock or reimburse
  • Overcharged FBA fees (wrong size tier)

Reimbursement Process

  1. Lost inventory: Check Inventory Reconciliation Report → file case if discrepancy
  2. Damaged by Amazon: Check FBA Customer Returns report → units marked "Damaged:Amazon" → file claim
  3. Customer return not received: Wait 45 days after return initiated → file claim if not processed
  4. Fee overcharge: Check FBA Fee Preview → measure product → file dispute if wrong tier

Time limits: Most claims must be filed within 18 months of incident

Tools: Sellerboard, Getida, GETIDA (recovery services that work on % of recovered amount)

Return Reduction Action Plan Template

Week 1: Audit
- Download return reason report (90 days)
- Identify top 3 return reasons
- Score each: fixable in listing vs. product vs. packaging

Week 2: Listing Fixes
- Update listing based on accuracy audit
- Add size comparison image
- Rewrite any misleading bullets

Week 3: Packaging Fix
- Order improved packaging materials
- Update FBA prep instructions

Week 4: Monitor
- Compare return rate to 30 days prior
- File any pending reimbursement claims
- Repeat monthly

Output Format

  1. Return Rate Diagnosis — which reasons are causing most returns
  2. Priority Fix List — top 3 changes ranked by impact
  3. Listing Accuracy Checklist — specific items to update
  4. Packaging Recommendations — if damage is a factor
  5. Reimbursement Opportunity — estimate of recoverable Amazon errors
  6. 30-Day Action Plan — week-by-week improvement roadmap

平台分布

OpenClaw

83.12%
按下载量换算1,383

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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