Quantity Take-Off (QTO) Report Generator for Openclaw

A high-performance tool for automating the extraction, grouping, and cost estimation of quantities from BIM and CAD datasets.

datadrivenconstruction
v2.1.0
Feb 16, 2026
0
1.6k
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install qto-report

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install qto-report using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Quantity Take-Off (QTO) Report Generator?

This skill provides a robust framework for generating comprehensive Quantity Take-Off (QTO) reports directly from BIM/CAD data. By leveraging Openclaw Skills, developers and construction professionals can automate the tedious process of manual quantity extraction, enabling high-precision 5D BIM workflows that integrate geometry, scheduling, and cost estimation.

The skill follows the Data-Driven Construction (DDC) methodology to organize BIM elements by category, level, or material. It supports multiple data sources including Revit CSV exports and IFC files via IfcOpenShell, making it an essential component for automated cost estimation and project planning in the AEC industry.

Quantity Take-Off (QTO) Report Generator Use Cases

  • Automating quantity extraction from Revit schedules and IFC models to reduce manual errors.
  • Generating multi-level QTO reports for complex construction projects requiring granular breakdowns.
  • Calculating 5D BIM cost estimates by applying unit prices to extracted volumes and areas.
  • Comparing design-phase quantities against as-built data to identify project variances.
  • Applying specific waste factors and calculation rules defined in external Excel files for local compliance.

How Quantity Take-Off (QTO) Report Generator Works

  1. Import BIM data from CSV or IFC files using specialized Python-based data processing logic.
  2. Clean and standardize element attributes such as Category, Level, Material, and Geometry parameters.
  3. Execute grouping and aggregation logic to sum volumes, areas, and element counts across the model.
  4. Apply cost calculation rules, unit prices, or waste factors to generate financial projections.
  5. Export the processed data into professional Excel reports, CSV files, or JSON for API and downstream tool integration.

Quantity Take-Off (QTO) Report Generator Setup

Ensure you have Python 3 installed on your system. This skill utilizes the Openclaw Skills ecosystem and requires specific libraries for data manipulation and IFC processing.

pip install pandas openpyxl ifcopenshell

Quantity Take-Off (QTO) Report Generator Data Schema & Taxonomy

The skill processes BIM element data into a structured format for reporting. The following table describes the standard output schema generated by the Openclaw Skills workflow:

Field Type Description
Category String BIM category classification (e.g., Wall, Floor, Column)
Volume Float Total calculated volume in cubic units
Area Float Total surface area in square units
Count Integer Total number of unique elements identified in the group
Total_Cost Float Calculated financial estimate (Quantity × Unit Price)
Material String Specific material assignment for detailed breakdown analysis

Quantity Take-Off (QTO) Report Generator Advanced Features

  • Multi-level grouping capabilities (Level > Category > Material) for deep data inspection.
  • Dynamic waste factor application to account for material loss during construction.
  • Automated pivot table generation for summarized executive reporting and dashboards.
  • Support for external rule-based calculation engines via direct Excel integration.
  • Integration ready for other Openclaw Skills focusing on 4D scheduling and carbon footprint analysis.

SKILL.md


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