A professional utility for extracting structured CAD data, including layers, blocks, and geometry, from DWG files into Excel spreadsheets without requiring AutoCAD.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install dwg-to-excel
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install dwg-to-excel 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 DWG to Excel Data Converter?
The DWG to Excel skill provides a high-performance solution for extracting rich data from AutoCAD files without the need for expensive CAD software licenses. By utilizing Openclaw Skills, users can transform proprietary DWG data into structured Excel databases, enabling seamless integration with other data analysis tools. This tool supports an extensive range of file versions from legacy R12 (1992) to the modern 2026 format, making it an essential component for firms managing diverse architectural and engineering data sets.
This skill is particularly valuable for developers building automated pipelines that require access to block attributes, text annotations, and geometric entities. Instead of relying on manual data entry or complex API integrations with proprietary CAD software, Openclaw Skills allow for a direct CLI or Python-based extraction process that is both fast and offline-capable.
DWG to Excel Data Converter Use Cases
- Performing automated layer audits to ensure project compliance with CAD standards.
- Generating detailed block schedules and inventory lists from floor plans and schematics.
- Extracting text annotations and dimensions for integration into project management databases.
- Comparing two versions of a drawing to identify additions, removals, and changes in geometry.
- Batch converting thousands of legacy DWG files into searchable Excel archives for data migration.
How DWG to Excel Data Converter Works
- The skill identifies the target DWG file and passes it to the DwgExporter CLI engine.
- The engine parses the DWG database to identify all internal entities, including layers, blocks, and text.
- It maps entity handles, coordinate systems (X, Y, Z), and specific attributes to a structured schema.
- An Excel file is generated containing specialized sheets for elements, layers, and block definitions.
- Optional PDF sheets are exported to provide a visual reference for the extracted data within the Openclaw Skills workflow.
DWG to Excel Data Converter Setup
To begin using this skill, ensure the DwgExporter executable is present on your system. You can interact with it via the CLI or Python.
# Basic CLI usage to convert a file
DwgExporter.exe "C:\Projects\FloorPlan.dwg"
# Convert and generate PDF layouts
DwgExporter.exe "C:\Projects\FloorPlan.dwg" sheets2pdf
For Python-based automation within Openclaw Skills, initialize the exporter class:
from dwg_exporter import DWGExporter
exporter = DWGExporter("path/to/DwgExporter.exe")
xlsx_path = exporter.convert("my_drawing.dwg")
DWG to Excel Data Converter Data Schema & Taxonomy
The output produced by Openclaw Skills is organized into a multi-sheet Excel workbook designed for easy programmatic consumption:
| Sheet | Description |
|---|---|
| Elements | All DWG entities (LINE, CIRCLE, INSERT, etc.) with their handles, layers, and coordinates. |
| Layers | A list of all layer names, visibility status (frozen/locked), colors, and entity counts. |
| Blocks | Definitions and metadata for all blocks found within the drawing. |
| Layouts | Data regarding the paper space layouts and sheet configurations. |
Each entity in the Elements sheet includes columns for Handle, EntityType, Layer, Color, and geometric data (X, Y, Z coordinates).
DWG to Excel Data Converter Advanced Features
- Comprehensive support for legacy and modern DWG formats spanning over 40 years (1983-2026).
- Advanced Python wrapper supporting entity-type statistics and block attribute extraction.
- Built-in drawing comparison tool to find differences in layer counts and entity types between revisions.
- Duplicate entity detection with configurable coordinate tolerance settings.
- Seamless batch processing capabilities for high-volume data extraction tasks using Openclaw Skills.
SKILL.md
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