Agent skill · data analytics · datadrivenconstruction
labor-productivity-analytics
Analyze construction labor productivity using data analytics. Track worker performance, identify inefficiencies, predict resource needs, and optimize crew allocation for maximum efficiency.
Why this skill is useful
Provides domain-specific analytics for construction labor productivity that the AI wouldn't reliably generate on its own.
What it needs
Requires python3 installed locally. About 7k tokens when loaded. Last updated 2026-02-14. 265 stars on the source repository.
What this skill does
Labor Productivity Analytics Overview This skill implements data-driven labor productivity analysis for construction projects. Track, measure, and optimize workforce performance to improve project efficiency and reduce costs. Capabilities: Productivity metrics calculation Time series analysis Crew optimization Resource forecasting Benchmarking Variance analysis Quick Start Comprehensive Productivity System Data Collection and Management Productivity Analysis Engine Resource Forecasting Reporting and Visualization Quick Reference Trade Typical Unit Rate Unit Notes ------- ------------------- ------ ------- Carpenter 0.5-1.0 m²/hr Formwork Ironworker 15-25 kg/hr Rebar tying Mason 0.3-0.5 m²/hr Brickwork Electrician 2-4 points/hr Rough-in Plumber 2-3 fixtures/hr Install Painter 3-5 m²/hr Interior Resources RS Means Labor Rates: Industry benchmarks AGC Productivity Standards: https://www.agc.org DDC Website: https://datadrivenconstruction.io
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills datadrivenconstruction/labor-productivity-analytics