ReddRadar
Agent skill
slotting-optimization-engine
AI-driven warehouse slotting skill to optimize product placement based on velocity, pick frequency, and operational efficiency
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/business/logistics/skills/slotting-optimization-engine
Metadata
Additional technical details for this skill
- domain
- business
- category
- warehouse
- priority
- medium
- specialization
- logistics
SKILL.md
Slotting Optimization Engine
Overview
The Slotting Optimization Engine is an AI-driven skill that optimizes warehouse product placement based on velocity, pick frequency, and operational efficiency. It analyzes product characteristics, order patterns, and warehouse layout to recommend optimal slot assignments that minimize travel time and maximize picking productivity.
Capabilities
- Velocity-Based Slot Assignment: Assign fast-moving items to prime picking locations based on historical velocity data
- Travel Distance Minimization: Optimize slot locations to reduce average travel distance per pick
- Ergonomic Zone Optimization: Place heavy or frequently picked items at ergonomically optimal heights to reduce worker strain
- Pick Path Efficiency Analysis: Analyze and optimize slot assignments based on typical pick path patterns
- Seasonal Demand Adjustment: Adjust slotting recommendations based on seasonal demand patterns and promotional calendars
- Product Affinity Clustering: Group frequently co-ordered items in proximity to reduce pick travel
- Golden Zone Placement: Strategically utilize prime picking zones for highest-velocity items
Tools and Libraries
- WMS APIs
- Slotting Optimization Algorithms
- Heuristic Solvers
- Data Analytics Libraries
Used By Processes
- Slotting Optimization
- Pick-Pack-Ship Operations
- Receiving and Putaway Optimization
Usage
skill: slotting-optimization-engine
inputs:
warehouse:
warehouse_id: "WH001"
zones:
- zone_id: "ZONE_A"
type: "pick_module"
locations: 500
golden_zone_locations: 100
- zone_id: "ZONE_B"
type: "bulk_storage"
locations: 200
products:
- sku: "SKU001"
velocity_class: "A"
picks_per_day: 150
cube: 0.5
weight_lbs: 2.5
stackable: true
- sku: "SKU002"
velocity_class: "B"
picks_per_day: 45
cube: 1.2
weight_lbs: 8.0
stackable: false
constraints:
optimize_for: "travel_time"
respect_product_families: true
ergonomic_weight_limit_lbs: 25
outputs:
slot_recommendations:
- sku: "SKU001"
recommended_location: "A-01-02-A"
zone: "ZONE_A"
reason: "High velocity - golden zone placement"
expected_picks_reduction: 15
- sku: "SKU002"
recommended_location: "A-05-03-B"
zone: "ZONE_A"
reason: "Medium velocity - mid-zone placement"
expected_picks_reduction: 8
projected_improvement:
travel_time_reduction_percent: 12.5
picks_per_hour_increase: 8.3
Integration Points
- Warehouse Management Systems (WMS)
- Inventory Management Systems
- Labor Management Systems
- Order Management Systems
- Slotting Analysis Tools
Performance Metrics
- Picks per hour improvement
- Travel distance reduction
- Slot utilization rate
- Replenishment frequency
- Ergonomic compliance rate
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
a5c-ai/babysitter
gsd-tools
Central utility skill for GSD operations. Provides config parsing, slug generation, timestamps, path operations, and orchestrates calls to other specialized skills. Acts as the unified entry point that the original gsd-tools.cjs provided via its lib/ modules (commands, config, core, init).
a5c-ai/babysitter
model-profile-resolution
Resolve model profile (quality/balanced/budget) at orchestration start and map agents to specific models. Enables cost/quality tradeoffs by selecting appropriate AI models for each agent role.
a5c-ai/babysitter
verification-suite
Plan structure validation, phase completeness checks, reference integrity verification, and artifact existence confirmation. Provides the structured verification layer ensuring GSD artifacts are well-formed and complete.
a5c-ai/babysitter
state-management
STATE.md reading, writing, and field-level updates. Provides cross-session state persistence via .planning/STATE.md with structured fields for current task, completed phases, blockers, decisions, and quick tasks.
a5c-ai/babysitter
git-integration
Git commit patterns, formats, and conventions for GSD methodology. Provides atomic commits per task, structured commit messages, planning file commits, branch management, and milestone tag operations.
a5c-ai/babysitter
frontmatter-parsing
YAML frontmatter parsing and manipulation for .planning/ documents. Provides read, write, update, query, and validation operations on frontmatter blocks in GSD markdown artifacts.
Didn't find tool you were looking for?