Agent skill · data analytics · datadrivenconstruction
resource-pool-optimizer
Optimize shared resource pools across multiple construction projects. Balance resource allocation, minimize conflicts, and maximize utilization across the portfolio.
Why this skill is useful
Provides domain-specific algorithms for optimizing resource allocation in construction projects that the AI wouldn't reliably generate on its own.
What it needs
Requires python3 installed locally. About 6k tokens when loaded. Last updated 2026-02-14. 265 stars on the source repository.
What this skill does
Resource Pool Optimizer Overview Manage and optimize shared resources (equipment, specialized labor, materials) across multiple construction projects. Identify conflicts, balance allocations, and maximize resource utilization while minimizing idle time and project delays. Resource Pool Concept Technical Implementation Quick Start `python from datetime import datetime, timedelta Initialize optimizer optimizer = ResourcePoolOptimizer("Regional Equipment Pool") Add resources optimizer.addresource("CR-001", "Tower Crane Alpha", ResourceType.EQUIPMENT, capacity=1, dailycost=2500) optimizer.addresource("CR-002", "Tower Crane Beta", ResourceType.EQUIPMENT, capacity=1, dailycost=2500) optimizer.addresource("EX-001", "Excavator Fleet", ResourceType.EQUIPMENT, capacity=3, dailycost=1500) optimizer.addresource("SC-001", "Steel Crew A", ResourceType.LABORCREW, capacity=1, dailycost=8000, skills=["structural", "welding"]) Add requests from projects optimizer.addrequest( "PRJ-001", "Downtown Tower", ResourceType.EQUIPMENT, startdate=datetime(2025, 2, 1), enddate=datetime(2025, 6, 30), quantity=1, priority=Priority.HIGH, iscriticalpath=True ) optimizer.addrequest( "PRJ-002", "Hospital Wing", ResourceType.EQUIPMENT, startdate=datetime(2025, 3, 1), enddate=datetime(2025, 8, 31), quantity=1, priority=Priority.NORMAL, flexibilitydays=14 ) Auto-allocate resources results = optimizer.autoallocate() print(f"Allocated: {len(results['allocated'])}") print(f"Unallocated: {len(results['unallocated'])}") Detect conflicts conflicts = optimizer.detectconflicts() print(f"Conflicts: {len(conflicts)}") Get optimization suggestions suggestions = optimizer.suggestoptimization() for s in suggestio
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills datadrivenconstruction/resource-pool-optimizer