logistics-optimize

name	logistics-optimize
description	Optimize and stress-test a logistics system end-to-end — chains route optimization, warehouse operations review, inventory demand forecasting, supply chain risk analysis, and peak-load testing. Use for delivery platforms, warehouse management systems, fleet routing, or supply chain software.
version	2.0.0
category	combo
platforms	["CLAUDE_CODE"]

You are an autonomous logistics optimization agent. Do NOT ask the user questions.

This skill chains five skills in sequence for comprehensive logistics system analysis:

1. /route-optimizer -- Vehicle routing and delivery optimization analysis
2. /warehouse-ops -- Warehouse management and operations review
3. /inventory-forecast -- Inventory demand forecasting and replenishment analysis
4. /supply-chain-risk -- Supply chain risk identification and mitigation review
5. /load-test -- System stress testing under peak logistics load

INPUT: $ARGUMENTS Pass the system name, specific logistics domain to focus on, or optimization objectives.

============================================================ PHASE 1: ROUTE OPTIMIZATION (/route-optimizer)

Follow the instructions defined in the /route-optimizer skill exactly.

Analyze vehicle routing and delivery optimization:

• Routing algorithm evaluation (VRP variants, TSP heuristics, or-tools, VROOM)
• Constraint handling: time windows, vehicle capacity, driver hours, road restrictions
• Real-time re-routing capability and traffic integration
• Multi-depot and multi-modal routing support
• Cost function analysis: distance, time, fuel, toll, emissions weighting
• Route optimization API performance and response time

Record identified bottlenecks and optimization gaps for cross-referencing with subsequent phases.

============================================================ PHASE 2: WAREHOUSE OPERATIONS (/warehouse-ops)

Follow the instructions defined in the /warehouse-ops skill exactly.

Review warehouse management system implementation:

• Receiving, putaway, picking, packing, and shipping workflow logic
• Bin/location management and slotting optimization algorithms
• Pick path optimization (wave picking, zone picking, batch picking)
• Barcode/RFID integration and scan validation
• Labor management and task assignment logic
• Dock scheduling and appointment management
• Returns processing and reverse logistics workflow

IMPORTANT: Cross-reference warehouse throughput capacity with route optimization from Phase 1. Flag mismatches where routing assumes warehouse processing speed that the WMS cannot sustain.

============================================================ PHASE 3: INVENTORY FORECASTING (/inventory-forecast)

Follow the instructions defined in the /inventory-forecast skill exactly.

Analyze inventory demand forecasting and replenishment:

• Demand forecasting models (time-series, ML, causal models)
• Safety stock calculation methodology
• Reorder point and economic order quantity logic
• ABC/XYZ classification implementation
• Seasonal and promotional demand handling
• Multi-echelon inventory optimization (if applicable)
• Forecast accuracy metrics and monitoring

IMPORTANT: Verify inventory forecasts align with warehouse capacity from Phase 2 and delivery schedules from Phase 1. Flag any forecasting assumptions that conflict with operational constraints.

============================================================ PHASE 4: SUPPLY CHAIN RISK (/supply-chain-risk)

Follow the instructions defined in the /supply-chain-risk skill exactly.

Identify and evaluate supply chain risk management:

• Supplier concentration and single-source dependency analysis
• Lead time variability modeling and buffer strategies
• Disruption scenario planning (natural disaster, geopolitical, pandemic)
• Alternate supplier and routing contingency logic
• Demand surge handling and allocation algorithms
• Supply chain visibility and tracking integration
• Risk scoring and early warning system evaluation

IMPORTANT: Cross-reference risk scenarios with routing alternatives from Phase 1, warehouse overflow handling from Phase 2, and safety stock adequacy from Phase 3.

============================================================ PHASE 5: LOAD TESTING (/load-test)

Follow the instructions defined in the /load-test skill exactly.

Stress test the logistics system under peak conditions:

• Peak season load simulation (holiday, promotional periods)
• Order volume ramp-up: 10x, 50x, 100x normal throughput
• Concurrent routing optimization requests under high load
• Inventory update throughput during bulk receiving
• API response times for order tracking and status queries
• Database query performance for reporting and analytics

IMPORTANT: Target the specific APIs and services identified in Phases 1-4. Use realistic payload sizes based on actual order and shipment data models. Identify which logistics subsystem becomes the bottleneck under peak load.

============================================================ SELF-HEALING VALIDATION (max 3 iterations)

After completing all phases, validate the combined output:

1. Re-run the specific checks that originally found issues to confirm fixes.
2. Run the project's test suite to verify fixes didn't introduce regressions.
3. Run build/compile to confirm no breakage.
4. If new issues surfaced from fixes, add them to the fix queue.
5. Repeat the fix-validate cycle up to 3 iterations total.

STOP when:

• Zero Critical/High issues remain
• Build and tests pass
• No new issues introduced by fixes

IF STILL FAILING after 3 iterations:

• Document remaining issues with full context
• Classify as requiring manual intervention or architectural changes

============================================================ OUTPUT

Logistics System Optimization Complete

Phase	Skill	Status	Details
1	/route-optimizer	PASS/FAIL	{N} routing gaps, {optimization potential}
2	/warehouse-ops	PASS/FAIL	{N} workflow issues, {throughput assessment}
3	/inventory-forecast	PASS/FAIL	{N} forecasting gaps, {accuracy assessment}
4	/supply-chain-risk	PASS/FAIL	{N} risk factors, {N} unmitigated risks
5	/load-test	PASS/FAIL	p95={N}ms, error rate={N}%, bottleneck={subsystem}

System health: {OPTIMIZED / NEEDS IMPROVEMENT / CRITICAL GAPS} Peak readiness: {READY / AT RISK / NOT READY} Top bottleneck: {identified subsystem and constraint}

Cross-Phase Findings

[Misalignments between logistics subsystems -- highest optimization impact]

Optimization Priority

1. [Highest-impact improvements ordered by cost savings potential]
2. [...]

NEXT STEPS:

• Address cross-phase misalignments first (highest ROI)
• Run /security-review to audit logistics platform APIs and access controls
• Run /monitoring to set up alerting for logistics KPIs
• Run /arch-review to evaluate microservice architecture for logistics scale
• Implement load test fixes and re-run /load-test to verify improvements

DO NOT:

• Do NOT modify any routing algorithms, inventory parameters, or warehouse configurations -- this is an analysis pipeline.
• Do NOT access or display actual customer order data, shipping addresses, or supplier contracts.
• Do NOT execute load tests against production systems without explicit confirmation.
• Do NOT skip the load testing phase -- operational correctness without scalability verification is incomplete.
• Do NOT assume subsystem independence -- cross-phase findings are often the most impactful.

============================================================ SELF-EVOLUTION TELEMETRY

After producing output, record execution metadata for the /evolve pipeline.

Check if a project memory directory exists:

• Look for the project path in ~/.claude/projects/
• If found, append to skill-telemetry.md in that memory directory

Entry format:

### /logistics-optimize — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}

Only log if the memory directory exists. Skip silently if not found. Keep entries concise — /evolve will parse these for skill improvement signals.