Metadata

name: Supply Chain & Logistics Intelligence
slug: supply-chain-intel
description: AI-powered global supply chain and logistics intelligence engine. Tracks ocean freight rates (Drewry/Freightos), port throughput (LA/LB, China ports), trade flows (UN Comtrade, US Census), transit times (Flexport OTI), equipment availability (Container xChange), and 5 major commodity bottlenecks (semiconductors, batteries, APIs, agriculture, rare earths). Monitors 14 risk factors (geopolitical, climate, labor, regulatory, cyber) across 4 logistics modes (air, ocean, rail, truck). Delivers real-time disruption alerts and cost optimization insights.
triggers: ["supply chain disruption","freight rates tracker","port congestion","trade flow analysis","logistics cost optimization","commodity bottleneck","shipping delay","supply chain risk assessment","inventory management","sourcing intelligence","customs clearance","3PL selection","warehouse location","supply chain resilience"]
author: Marvis
version: 1.0
metadata: {"emoji":"🚢","requires":"references/supply_chain_sources.json"}

Supply Chain & Logistics Intelligence

Capabilities

#	Capability	Input	Output
1	Freight Rate Dashboard	Route (e.g., Shanghai-LA) / mode (ocean/air)	Spot rate, 1Y range, trend, capacity outlook, booking lead time
2	Port Congestion Monitor	Port(s) / region	Vessel queue length, dwell time, gate hours, labor status, weather impact
3	Trade Flow Analyzer	Country pair / commodity (HS code)	Volume, value, growth rate, seasonality, tariff impact, alternative routes
4	Commodity Bottleneck Scanner	Commodity (semiconductors, batteries, etc)	Key suppliers, geographic concentration, lead time, price volatility, substitution options
5	Supply Chain Risk Heatmap	Company / product / region	Geopolitical risk, climate exposure, labor disruption probability, regulatory compliance burden
6	Transit Time Estimator	Origin-destination + mode	Current transit days, historical variability, delay probability, expedited options cost
7	Inventory Optimization Model	Demand forecast + lead time variability	Safety stock level, reorder point, EOQ, service level vs. carrying cost trade-off
8	Sourcing Intelligence	Component / raw material	Supplier landscape, pricing benchmarks, quality ratings, ESG compliance, dual-sourcing feasibility
9	Logistics Cost Benchmark	Shipment profile (weight, volume, value)	Cost breakdown (freight, fuel surcharge, customs, insurance), vs. industry average
10	Disruption Alert System	Watchlist (ports, suppliers, routes)	Real-time alerts (strikes, weather, sanctions), impact assessment, contingency plan suggestions

Workflow

User Query
  │
  ├─ [Step 1] Classify → logistics mode + commodity + geography + time horizon
  │
  ├─ [Step 2] Multi-source data retrieval:
  │   └─ Freight rates: Drewry, Freightos
  │   └─ Port data: Port of LA/LB, China Ports Association
  │   └─ Trade: UN Comtrade, US Census
  │   └─ Risk: Resilinc, Bloomberg SCM
  │   └─ Equipment: Container xChange
  │
  ├─ [Step 3] Cross-validate & flag discrepancies
  │
  ├─ [Step 4] Apply supply chain models:
  │   └─ Inventory optimization (EOQ, safety stock)
  │   └─ Network design (facility location, routing)
  │   └─ Risk quantification (VaR for lead time)
  │
  ├─ [Step 5] Generate structured output with actionable insights
  │
  └─ [Step 6] Cite data vintage, source URLs, confidence intervals

Output Formats

Freight Rate Snapshot

Route	Mode	Spot Rate	1W Change	1Y Range	Capacity	Booking Lead Time
Shanghai-LA	Ocean	$X,XXX/TEU	+X%	$X,XXX-$X,XXX	Tight	3-4 weeks
Frankfurt-ORD	Air	$X.XX/kg	-X%	$X.XX-$X.XX	Available	1-2 days

Port Congestion Dashboard

Port	Vessels Waiting	Avg Dwell Time (days)	Gate Hours	Labor Status	Weather Alert
Los Angeles	12	4.2	24/7	Normal	None
Rotterdam	8	3.8	6am-10pm	Strike warning	High winds

Commodity Bottleneck Matrix

Commodity	Key Suppliers	Geographic Risk	Lead Time (weeks)	Price Volatility	Substitution Options
Advanced Semiconductors	TSMC, Samsung, Intel	Taiwan Strait, US-China	26-52	High	None (critical)
Lithium-ion Batteries	CATL, LG, Panasonic	China, DRC, Chile	12-24	Medium	Sodium-ion (emerging)

Usage Guidelines

Real-time data priority — supply chain data decays rapidly; flag any data >7 days old
Multi-modal comparison — always present air vs. ocean vs. rail trade-offs (cost vs. speed vs. reliability)
Risk quantification — express disruptions in $ impact and lead time extension, not just qualitative
Actionable recommendations — each insight should link to a decision (reroute, expedite, buffer stock, dual-source)
Regulatory compliance — include customs, sanctions (OFAC), forced labor (UFLPA), carbon border (CBAM) considerations
Scenario planning — provide best-case/worst-case/base-case for critical decisions

Examples

Example 1: Freight Cost Optimization

User: "Best way to ship 100 TEU from Shenzhen to Chicago in Q3 2026?" Output: Ocean vs. rail vs. air cost/speed comparison; port pair recommendations (Shenzhen→LA vs. Shenzhen→Vancouver); transit time variability; fuel surcharge forecast; contingency for Panama Canal drought.

Example 2: Disruption Impact Assessment

User: "What's the impact of a potential ILWU strike at LA/LB ports?" Output: Historical strike duration (days), backlog buildup rate (TEU/day), alternative ports (Oakland, Tacoma, Mexico), cost premium for air freight, inventory burn-down timeline for key industries.

Example 3: Sourcing Strategy

User: "Should we dual-source rare earth magnets from China and Vietnam?" Output: Supplier capability comparison, quality variance, lead time differential, tariff implications, ESG risk (China Xinjiang concerns), total landed cost model.

Data Base: references/supply_chain_sources.json — 14 authoritative data sources, 5 key commodities, 5 risk factors, 4 logistics modes. Last Updated: June 2026 Free Tier: Available. This skill aggregates public supply chain data; no proprietary carrier contracts accessed.

Supply Chain & Logistics Intelligencel

安装技能