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Agent Skill · 待分类

supply-chain-optimizer(供应链优化器)

supply-chain-optimizer 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

supply-chain-optimizer 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为权限未标注;许可证信息还不明确,第三方扫描已通过,按安装量在待分类类的 11,209 个 Skill 里排第 1,389。

总安装 3,539周安装 152GitHub Stars 48下载 1,240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
unknown

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:supply-chain-optimizer(供应链优化器)
来源仓库:https://github.com/travisjneuman/.claude
仓库路径:skills/supply-chain-optimizer
安装命令:
npx skills add https://github.com/travisjneuman/.claude --skill supply-chain-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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/travisjneuman/.claude --skill supply-chain-optimizer

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

supply-chain-optimizer 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态和代码变更进行整理。支持查询协作事项、代码变更历史和仓库维护状态等 GitHub 相关操作。

安装前需确认权限范围和维护状态,注意是否会触发联网或命令执行。建议结合原始 README 核验具体用法,避免直接依赖未经验证的输出结果。

来源仓库内路径:skills/supply-chain-optimizer

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/travisjneuman/.claude --skill supply-chain-opt…;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

    权限没有明确标注,第一次使用时只给一个无关紧要的任务,观察它到底读了哪些文件和网络。

常见问题

6 条

supply-chain-optimizer 怎么安装?

在终端执行 npx skills add https://github.com/travisjneuman/.claude --skill supply-chain-optimizer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

supply-chain-optimizer 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

supply-chain-optimizer 需要什么权限?

权限级别没有明确标注。第一次使用时建议只给无关紧要的任务,观察它实际读写了哪些内容。

supply-chain-optimizer 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

supply-chain-optimizer 用的人多吗?

公开数据是累计安装 3,539 次,近一周安装 152 次,下载 1,240 次,GitHub 48 星。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。

supply-chain-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

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 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

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
supply-chain-optimizer

供应链优化器 · 本页

3,53948权限未标注未明确通过

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
supply-chain-optimizer
description
Supply chain analysis, inventory optimization, logistics planning, vendor evaluation, and demand forecasting frameworks. Use when analyzing supply chains, optimizing inventory, or evaluating suppliers.

Supply Chain Optimizer

Comprehensive frameworks for supply chain analysis, inventory management, logistics optimization, and vendor evaluation.

Supply Chain Mapping Template

End-to-End Supply Chain Map

RAW MATERIALS → SUPPLIERS → MANUFACTURING → DISTRIBUTION → CUSTOMER

MAPPING STEPS:
1. Identify all nodes (suppliers, plants, warehouses, customers)
2. Map material flows between nodes
3. Map information flows (orders, forecasts, POs)
4. Map financial flows (payments, invoicing)
5. Record lead times at each stage
6. Identify bottlenecks and single points of failure

NODE DETAIL TEMPLATE:
| Node           | Type       | Location  | Lead Time | Capacity | Utilization |
| -------------- | ---------- | --------- | --------- | -------- | ----------- |
|                | Supplier   |           |           |          |             |
|                | Plant      |           |           |          |             |
|                | Warehouse  |           |           |          |             |
|                | DC         |           |           |          |             |

Inventory Optimization

Economic Order Quantity (EOQ)

EOQ = sqrt(2DS / H)

Where: D = Annual demand, S = Ordering cost/order, H = Holding cost/unit/year
Total Cost = (D/Q)S + (Q/2)H + DC

Example: D=10,000, S=$50, H=$5 → EOQ = 447 units, 22.4 orders/year

Safety Stock & Reorder Point

SAFETY STOCK: SS = z x sigma_dLT
REORDER POINT: ROP = (Avg Daily Demand x Lead Time) + Safety Stock

SERVICE LEVEL FACTORS:
| Service Level | z-Score | Use Case          |
| ------------- | ------- | ----------------- |
| 90.0%         | 1.28    | Basic coverage    |
| 95.0%         | 1.65    | Standard          |
| 99.0%         | 2.33    | High service      |
| 99.9%         | 3.09    | Critical items    |

Inventory KPI Dashboard

MetricFormulaTarget
Inventory TurnsCOGS / Average InventoryIndustry-specific
Days of SupplyAverage Inventory / (COGS / 365)Minimize
Fill RateOrders Filled Complete / Total Orders97%+
Stockout RateStockout Events / Total Demand Events< 2%
Carrying Cost %Holding Costs / Average Inventory Value15-30%
Dead Stock %No-movement Items / Total SKUs< 5%
Inventory AccuracyCorrect Counts / Total Counts99%+
GMROIGross Margin / Average Inventory Cost> 2.0

ABC-XYZ Analysis Framework

ABC CLASSIFICATION (Value):
A Items: Top 20% of SKUs = ~80% of annual consumption value
  → Tight control, frequent review, accurate forecasts
B Items: Next 30% of SKUs = ~15% of value
  → Moderate control, periodic review
C Items: Bottom 50% of SKUs = ~5% of value
  → Minimal control, simple replenishment rules

XYZ CLASSIFICATION (Demand Variability):
X: Coefficient of Variation < 0.5 → Stable, predictable demand
Y: CV between 0.5 and 1.0 → Some variation, trend/seasonal
Z: CV > 1.0 → Highly irregular, sporadic demand

COMBINED MATRIX:
| Class | AX         | AY           | AZ            |
| ----- | ---------- | ------------ | ------------- |
| Strat | JIT/Kanban | Forecast     | Order on demand|
| Class | BX         | BY           | BZ            |
| Strat | Reorder pt | Buffer stock | Min/Max       |
| Class | CX         | CY           | CZ            |
| Strat | Bulk buy   | Periodic rev | Eliminate?     |

Vendor Scorecard

Supplier Evaluation Matrix

CriteriaWeightScore (1-5)Weighted ScoreNotes
Quality (PPM)25%
Delivery (OTIF)20%
Pricing20%
Responsiveness10%
Financial Health10%
Innovation5%
Sustainability5%
Risk Profile5%
Total100%__ / 5.0
RATING SCALE:
4.5-5.0  Strategic Partner — expand relationship
3.5-4.4  Preferred Supplier — maintain, develop
2.5-3.4  Approved Supplier — improvement plan required
< 2.5    Probation / Exit — find alternative

Supplier Performance Tracking

KPITargetQ1 ActualQ2 ActualQ3 ActualQ4 ActualTrend
On-Time Delivery98%+
Quality (PPM)< 500
Lead Time (days)
Price Variance+/- 2%
Response Time (hrs)< 24
Corrective Actions< 2/qtr

Total Cost of Ownership (TCO)

TCO = Acquisition Costs + Operating Costs + Disposal Costs

ACQUISITION COSTS:
  Purchase price
+ Shipping / freight
+ Customs / duties / tariffs
+ Procurement labor
+ Quality inspection
+ Supplier qualification
= Total Acquisition

OPERATING COSTS (over useful life):
  Maintenance & repair
+ Inventory carrying cost
+ Warranty claims
+ Downtime cost (if component fails)
+ Training / support
+ Quality failures (scrap, rework)
= Total Operating

DISPOSAL COSTS:
  Decommissioning
+ Recycling / disposal fees
+ Environmental compliance
= Total Disposal

TCO = Total Acquisition + Total Operating + Total Disposal

TCO Comparison Template

Cost ElementSupplier ASupplier BSupplier C
Unit Price
Shipping
Duties / Tariffs
Quality Cost (est.)
Inventory Carry Cost
Lead Time Cost
Risk Premium
Total TCO/Unit
Annual TCO

Demand Forecasting Methods

MethodBest ForHorizonData Required
Moving AverageStable demandShort-term3-12 periods history
Exponential SmoothTrend detectionShort-termRecent weighted data
Holt-WintersSeasonal patternsMedium-term2+ years seasonal
Linear RegressionTrend with causal factorsMedium-termDemand + drivers
ARIMAComplex time seriesShort-medium50+ data points
Machine LearningMulti-variable patternsAnyLarge datasets
Delphi / ExpertNew products, disruptionsLong-termExpert panel

Forecast Accuracy Metrics

MAD (Mean Absolute Deviation):
MAD = (1/n) x SUM(|Actual - Forecast|)

MAPE (Mean Absolute Percentage Error):
MAPE = (1/n) x SUM(|Actual - Forecast| / Actual) x 100

BIAS (Tracking Signal):
Bias = SUM(Actual - Forecast) / MAD
Target: Between -4 and +4

ACCURACY BENCHMARKS:
| Forecast Horizon | Good MAPE | Acceptable MAPE |
| ---------------- | --------- | --------------- |
| 1 month          | < 15%     | < 25%           |
| 3 months         | < 25%     | < 35%           |
| 6 months         | < 30%     | < 45%           |
| 12 months        | < 35%     | < 50%           |

Logistics Optimization

Transportation Mode Selection

ModeCost/UnitSpeedCapacityBest For
TruckMediumFastMediumRegional, door-to-door
RailLowSlowVery HighBulk, long-distance domestic
OceanVery LowVery SlowVery HighInternational, bulk cargo
AirVery HighVery FastLowHigh-value, urgent, perishable
IntermodalLow-MedMediumHighLong-distance, cost-effective

Warehouse Layout Optimization

SLOTTING STRATEGY:
Fast movers (A items) → Near shipping dock, prime pick locations
Medium movers (B items) → Middle zones
Slow movers (C items) → High racks, far locations

LAYOUT PRINCIPLES:
1. Minimize travel distance for highest-velocity items
2. Group items frequently ordered together
3. Separate receiving and shipping areas
4. Reserve staging areas for cross-docking
5. Maintain clear aisle widths for equipment

Lead Time Analysis

TOTAL LEAD TIME:
Order Processing Time
+ Supplier Manufacturing Time
+ Transportation Time
+ Receiving / Inspection Time
+ Internal Processing Time
= Total Lead Time

LEAD TIME VARIABILITY:
Track actual vs. quoted lead times over 12+ orders
Calculate standard deviation
Use for safety stock calculations

LEAD TIME REDUCTION STRATEGIES:
| Strategy              | Typical Reduction | Effort    |
| --------------------- | ----------------- | --------- |
| Vendor-managed inv.   | 30-50%            | Medium    |
| Local sourcing        | 40-70%            | High      |
| Process automation    | 10-30%            | Medium    |
| Blanket POs           | 20-40%            | Low       |
| Consignment stock     | 50-80%            | Medium    |
| 3PL consolidation     | 10-25%            | Low       |

Supply Chain Risk Assessment

Risk Identification Matrix

Risk CategoryRisk EventLikelihoodImpactScoreMitigation
SupplySingle-source failureDual-source
DemandDemand spike/collapseBuffer stock, flex
LogisticsPort congestionAlternate routes
GeopoliticalTariffs, sanctionsNearshoring
Natural DisasterEarthquake, floodGeographic diversity
CyberSystem breachSecurity protocols
QualityBatch failureInspection, redundancy
FinancialSupplier bankruptcyFinancial monitoring
RISK SCORING:
Likelihood: 1 (Rare) to 5 (Almost Certain)
Impact: 1 (Negligible) to 5 (Catastrophic)
Risk Score = Likelihood x Impact

ACTION THRESHOLDS:
20-25  Critical — immediate action, executive attention
12-19  High — mitigation plan required within 30 days
6-11   Medium — monitor quarterly, contingency plans
1-5    Low — accept or monitor annually

KPI Dashboard Template

CategoryKPITarget
CostSC Cost as % of Revenue5-10%
CostCost per OrderMinimize
ServicePerfect Order Rate95%+
ServiceOn-Time In-Full (OTIF)98%+
ServiceCustomer Fill Rate97%+
EfficiencyInventory TurnsIndustry-specific
EfficiencyCash-to-Cash CycleMinimize
EfficiencyWarehouse Utilization85%
EfficiencyForecast Accuracy (MAPE)< 20%

See Also

平台分布

Codex

37.37%
按下载量换算463

Claude

28.06%
按下载量换算348

Cursor

18.08%
按下载量换算224

Gemini CLI

8.64%
按下载量换算107

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

权限未标注

当前来源未能明确判断权限范围,默认进入异常复核队列。

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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