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Agent Skill · 效率

amazon-inventory-forecast(亚马逊库存预测)

amazon-inventory-forecast 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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-inventory-forecast 是效率类 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,按安装量在效率类的 21,003 个 Skill 里排第 3,978。

总安装 14,801周安装 593GitHub Stars 公开资料未说明下载 4,791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-inventory-forecast(亚马逊库存预测)
来源仓库:https://github.com/mguozhen/amazon-inventory-forecast
安装命令:
openclaw skills install amazon-inventory-forecast
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-inventory-forecast

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

根据销售速度与交货时间预测最佳再订购点与库存数量。帮助卖家降低缺货风险并优化仓储成本。amazon-inventory-forecast 属于效率类 Skill,可作为该场景下的辅助能力补充。结合存储费用与销售趋势生成补货建议。

安装命令:openclaw skills install amazon-inventory-forecast。需验证输入数据的准确性,避免错误预测导致库存积压。

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-inventory-forecast;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-inventory-forecast 怎么安装?

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

amazon-inventory-forecast 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-inventory-forecast 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-inventory-forecast 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-inventory-forecast 用的人多吗?

公开数据是累计安装 14,801 次,近一周安装 593 次,下载 4,791 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-inventory-forecast 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。
  • 需要处理效率类任务、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。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
amazon-inventory-forecast

亚马逊库存预测 · 本页

14,801—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-inventory-forecast
description
Amazon inventory forecasting agent. Calculates optimal reorder points and quantities from sales velocity, lead time, and storage costs — tells sellers exactly when to reorder and how much to order. Triggers: inventory forecast, reorder point, stock forecast, amazon inventory, fba inventory, stockout prevention, overstock, safety stock, eoq, inventory management, when to reorder, inventory calculator
allowed-tools
Bash
metadata
openclaw
homepage
https://github.com/mguozhen/amazon-inventory-forecast

Amazon Inventory Forecast

FBA inventory intelligence — know exactly when to reorder and how much to order before you stock out or overstock.

Provide your sales data, lead time, and current stock levels. The agent calculates reorder points, EOQ, stockout risk windows, and storage fee exposure.

Commands

forecast add <sku>                 # add a SKU to track with sales and lead time data
forecast check                     # run forecast update on all tracked SKUs
forecast reorder point             # calculate reorder point for each SKU
forecast eoq                       # calculate economic order quantity
forecast stockout risk             # identify SKUs at risk of stocking out
forecast overstock risk            # identify SKUs at risk of long-term storage fees
forecast report                    # full inventory health report
forecast save                      # save all SKU data and forecasts to workspace

What Data to Provide

The agent works with:

  • SKU + sales data — "SKU: B-RED-LG, sold 240 units last 30 days, currently 180 units on hand"
  • Lead time — "supplier takes 25 days to ship, FBA check-in adds 5 days"
  • Storage cost — monthly FBA storage fee rate (standard or oversized)
  • Unit cost — your landed cost per unit (for EOQ calculation)
  • Seasonal notes — "Q4 demand doubles, Prime Day adds ~3x spike"

No integrations needed. Paste your data directly.

Workspace

Creates ~/amazon-inventory/ containing:

  • skus.md — tracked SKUs with sales history and parameters
  • forecasts/ — generated forecast reports per SKU
  • alerts.md — stockout and overstock alert log
  • reorder-log.md — history of reorder recommendations made

Analysis Framework

1. Sales Velocity Calculation

  • Compute average daily sales from 30-day, 60-day, and 90-day windows
  • Weight recent data more heavily: 30-day gets 50%, 60-day gets 30%, 90-day gets 20%
  • Weighted daily sales = (30d avg × 0.5) + (60d avg × 0.3) + (90d avg × 0.2)
  • Flag: high variance between windows — demand is trending up or down
  • Flag: 30d velocity >20% above 90d average — demand acceleration detected

2. Lead Time Buffer Calculation

  • Total lead time = supplier processing + shipping transit + FBA check-in buffer
  • Default FBA check-in buffer: 7 days (use 10 days during Oct–Dec peak season)
  • Safety stock formula: Safety Stock = Z-score × σ(daily demand) × √(lead time)
  • Conservative Z-score = 1.65 (95% service level); aggressive = 1.28 (90%)
  • Minimum safety stock: 14 days of average daily sales

3. Reorder Point Formula

  • Reorder Point = (Average Daily Sales × Total Lead Time) + Safety Stock
  • Example: 8 units/day × 30 days lead time + 56 units safety stock = 296 units
  • Express reorder point both in units and in days-of-stock-remaining
  • Show the calculation explicitly so sellers can verify inputs

4. EOQ Formula (Economic Order Quantity)

  • EOQ = √(2DS / H)

- D = annual demand (units/year) - S = order cost per purchase order (shipping + prep + admin, typically $50–$200) - H = annual holding cost per unit (FBA storage fee × 12 + opportunity cost)

  • Round EOQ up to nearest full case pack quantity
  • Show sensitivity analysis: EOQ at ±20% demand change

5. Storage Fee Avoidance

  • FBA long-term storage fee triggers: units stored >365 days
  • Q4 surcharge period: Oct 1 – Dec 31 (higher monthly rates)
  • Q4 inventory removal deadline: recommend sending final Q4 shipment no later than Sept 15
  • Overstock flag: current inventory > 180 days of supply at current velocity
  • Compute projected months-of-supply: Current Stock / (Daily Sales × 30)

6. Demand Seasonality Adjustments

  • Apply seasonal multipliers when user provides them
  • Common multipliers: Q4 holiday = 1.5–3x, Prime Day = 2–4x (48-hour window), Back-to-school = 1.2–1.5x
  • Adjusted forecast = base velocity × seasonal multiplier
  • For Q4 planning: build to cover Oct 1 – Dec 31 + post-holiday return buffer
  • Flag: if current stock will not cover a known seasonal spike, surface reorder urgency

Reorder Decision Output

Every forecast check shows per SKU:

SKUDaily SalesDays of StockReorder PointEOQStatus
...............OK / REORDER NOW / URGENT

Status levels:

  • OK — days of stock > reorder point days
  • REORDER SOON — within 14 days of reorder point
  • REORDER NOW — at or below reorder point
  • URGENT — less than lead time days of stock remaining (stockout imminent)

Rules

  1. Always collect lead time before computing reorder points — the formula is useless without it
  2. Never recommend a reorder quantity below one full case pack — partial cases create receiving complications at FBA
  3. Flag all assumptions explicitly — if the user has not provided 90-day sales data, state which averages were used
  4. Apply Q4 seasonality adjustments automatically for any forecast that spans October–December
  5. Show the full math for every EOQ and reorder point calculation — sellers need to verify with their own numbers
  6. Distinguish between units currently at FBA and units in transit — both count toward days-of-supply
  7. Save updated forecasts to ~/amazon-inventory/forecasts/ on every forecast save call

平台分布

OpenClaw

87.41%
按下载量换算4,188

安全审计

VirusTotal

未展示

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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