Cwicr Takeoff Helper
Assist with quantity takeoff using CWICR data. Calculate quantities from dimensions, apply waste factors, and suggest related work items.
Why use this skill?
Automate construction quantity takeoffs with the CWICR Takeoff Helper. Calculate material quantities, apply waste factors, and ensure scope completeness.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/datadrivenconstruction/cwicr-takeoff-helperWhat This Skill Does
The Cwicr Takeoff Helper is a specialized AI agent skill designed to streamline the quantity takeoff process for construction projects. By leveraging the CWICR (Construction Work Item Calculation Reference) methodology, this skill transforms raw dimensional data into professional-grade material estimates. It automates complex unit conversions between metric and imperial systems, applies industry-standard waste factors based on material category, and performs precise calculations for linear, area, volume, count, and weight-based takeoffs. Beyond simple math, the skill acts as a proactive assistant by suggesting related work items, helping project managers and estimators ensure scope completeness and avoid costly omissions during the bidding phase.
Installation
To integrate this skill into your environment, run the following command in your terminal: clawhub install openclaw/skills/skills/datadrivenconstruction/cwicr-takeoff-helper
Use Cases
- Project Bidding: Quickly generate bill of materials (BOM) estimates from blueprints or site measurements to improve bid turnaround times.
- Scope Gap Analysis: Automatically suggest necessary secondary work items (e.g., suggesting mortar when calculating brick masonry) to prevent scope creep or missing line items.
- Multi-Unit Estimation: Easily toggle between SI and Imperial units for international projects or specific regional code requirements.
- Material Procurement: Calculate precise ordering quantities by factoring in default waste margins tailored to specific material types like drywall, rebar, or concrete.
Example Prompts
- "I need to calculate the volume of concrete for a 20ft x 15ft slab that is 8 inches thick. Please apply the standard concrete waste factor and suggest related formwork or reinforcement items."
- "Calculate the total linear meters of pipe needed for a 50-foot run, convert to meters, and add a 5% waste factor."
- "I have 500 square feet of flooring to install. What are the related items I should include in my estimate, such as adhesives or transitions?"
Tips & Limitations
- Precision: While the helper uses precise conversion factors, always verify output against local building codes and site-specific conditions, as actual waste factors may vary based on site logistics.
- Scope: The skill is designed to assist with estimation and is not a substitute for professional engineering sign-off on structural load calculations.
- Data Integrity: Ensure that input dimensions are consistent in unit type to avoid calculation errors. The tool works best when provided with structured input.
- Waste Factors: Users can adjust default waste factors if they have historical performance data that differs from the provided standards.
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-cwicr-takeoff-helper": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: 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.