Productivity Analyzer
Analyze labor productivity from site data. Compare planned vs actual, identify trends, benchmark against industry standards.
Why use this skill?
Analyze construction labor productivity, compare actual vs planned output, and track project trends using industry-standard benchmarks.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/datadrivenconstruction/productivity-analyzerWhat This Skill Does
The Productivity Analyzer is a sophisticated engine designed for the construction and heavy industry sectors. It processes granular field reports to calculate labor efficiency, allowing project managers to bridge the gap between initial estimates and real-world performance. By ingesting daily logs—including planned versus actual output, man-hours, and crew sizes—the tool provides a comprehensive health check on ongoing site activities. It utilizes industry-standard benchmarks for common tasks like concrete pouring, rebar installation, and excavation to determine if your crew is meeting expected output-per-man-hour targets. The system categorizes performance into statuses (Excellent, On Target, Below, or Critical) and tracks historical trends, helping you identify whether a specific activity is improving or trending toward a schedule slip.
Installation
To integrate this agent skill into your OpenClaw environment, execute the following command in your terminal:
clawhub install openclaw/skills/skills/datadrivenconstruction/productivity-analyzer
Ensure you have the necessary permissions within your current project directory before running the command to allow the skill to populate its internal data structures.
Use Cases
- Project Forecasting: Predict remaining project duration based on current actual rates rather than optimistic planned estimates.
- Bottleneck Identification: Pinpoint which activities or conditions (e.g., weather or site access issues) are significantly lowering production rates.
- Performance Review: Benchmark specific crew output against industry standards to identify training needs or logistical improvements.
- Resource Optimization: Analyze the correlation between crew size and output to determine the optimal number of workers for specific tasks.
Example Prompts
- "Analyze the productivity for the concrete pouring activity over the last two weeks and tell me if we are trending toward a delay."
- "Compare our current rebar installation efficiency against industry benchmarks and categorize any tasks below 70% as critical."
- "Summarize the impact of site conditions on our drywall productivity rates and identify the top three factors hindering our performance."
Tips & Limitations
- Data Integrity: The accuracy of your analysis depends entirely on the precision of your input data. Ensure man-hours and output units are recorded consistently.
- Context Matters: While the tool identifies trends, always account for qualitative data in the 'conditions' field. Productivity dips are often valid (e.g., severe weather) rather than reflective of poor performance.
- Scope: This tool is optimized for repetitive construction tasks defined in the benchmark list; it may require custom adjustment for unique, custom-engineered work phases.
Metadata
Not sure this is the right skill?
Describe what you want to build — we'll match you to the best skill from 16,000+ options.
Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-datadrivenconstruction-productivity-analyzer": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: file-read, code-execution
Related Skills
data-lineage-tracker
Track data origin, transformations, and flow through construction systems. Essential for audit trails, compliance, and debugging data issues.
cwicr-cost-calculator
Calculate construction costs using DDC CWICR resource-based methodology. Break down costs into labor, materials, equipment with transparent pricing.
data-anomaly-detector
Detect anomalies and outliers in construction data: unusual costs, schedule variances, productivity spikes. Statistical and ML-based detection methods.
historical-cost-analyzer
Analyze historical construction costs for benchmarking, trend analysis, and estimating calibration. Compare projects, track escalation, identify patterns.
df-merger
Merge pandas DataFrames from multiple construction sources. Handle different schemas, keys, and data quality issues.