Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill dwg-to-excelgit clone --depth 1 https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_ConstructionWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/dwg-to-excel)<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/dwg-to-excel"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/dwg-to-excel/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/dwg-to-excel"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/dwg-to-excel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.03870 |
| Opus 5.5 | $0.00017 | $0.01548 |
| Sonnet 5.5 | $0.00008 | $0.00774 |
| Haiku 4.5 | $0.00004 | $0.00387 |
Grade A, and why
dwg-to-excel scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
result = subprocess.run(cmd, capture_output=True, text=True) Copies of this mod
1 near-identical copy found in the catalogue:
- dwg-to-excel — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 505 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DWG to Excel Conversion
Business Case
Problem Statement
AutoCAD DWG files contain valuable project data locked in proprietary format:
- Layer structures with drawing organization
- Block references with attribute data
- Text annotations and dimensions
- Geometric entities (lines, polylines, arcs)
- External references (xrefs)
Extracting this data typically requires AutoCAD licenses or complex programming.
Solution
DwgExporter.exe converts DWG files to structured Excel databases offline, without Autodesk licenses.
Business Value
- Zero license cost - No AutoCAD license required
- Legacy support - Reads DWG files from 1983 to 2026
- Data extraction - Layers, blocks, attributes, text, geometry
- PDF export - Generate drawings from DWG layouts
- Batch processing - Convert thousands of DWG files
Technical Implementation
CLI Syntax
DwgExporter.exe <input_dwg> [options]
Output Formats
| Output | Description |
|---|---|
.xlsx |
Excel database with all entities |
.pdf |
PDF drawings from layouts |
Supported Versions
| Version Range | Description |
|---|---|
| R12 (1992) | Legacy DWG |
| R14 (1997) | AutoCAD 14 |
| 2000-2002 | DWG 2000 format |
| 2004-2006 | DWG 2004 format |
| 2007-2009 | DWG 2007 format |
| 2010-2012 | DWG 2010 format |
| 2013-2017 | DWG 2013 format |
| 2018-2026 | DWG 2018 format |
Examples
# Basic conversion
DwgExporter.exe "C:\Projects\FloorPlan.dwg"
# Export with PDF drawings
DwgExporter.exe "C:\Projects\FloorPlan.dwg" sheets2pdf
# Batch processing all DWG in folder
for /R "C:\Projects" %f in (*.dwg) do DwgExporter.exe "%f"
# PowerShell batch conversion
Get-ChildItem "C:\Projects\*.dwg" -Recurse | ForEach-Object {
& "C:\DDC\DwgExporter.exe" $_.FullName
}
Python Integration
import subprocess
import pandas as pd
from pathlib import Path
from typing import List, Optional, Dict, Any
from dataclasses import dataclass
from enum import Enum
class DWGEntityType(Enum):
"""DWG entity types."""
LINE = "LINE"
POLYLINE = "POLYLINE"
LWPOLYLINE = "LWPOLYLINE"
CIRCLE = "CIRCLE"
ARC = "ARC"
ELLIPSE = "ELLIPSE"
SPLINE = "SPLINE"
TEXT = "TEXT"
MTEXT = "MTEXT"
DIMENSION = "DIMENSION"
INSERT = "INSERT" # Block reference
HATCH = "HATCH"
SOLID = "SOLID"
POINT = "POINT"
ATTRIB = "ATTRIB"
ATTDEF = "ATTDEF"
@dataclass
class DWGEntity:
"""Represents a DWG entity."""
handle: str
entity_type: str
layer: str
color: int
linetype: str
lineweight: float
# Geometry (depends on entity type)
start_x: Optional[float] = None
start_y: Optional[float] = None
end_x: Optional[float] = None
end_y: Optional[float] = None
# Block reference data
block_name: Optional[str] = None
rotation: Optional[float] = None
scale_x: Optional[float] = None
scale_y: Optional[float] = None
# Text data
text_content: Optional[str] = None
text_height: Optional[float] = None
@dataclass
class DWGBlock:
"""Represents a DWG block definition."""
name: str
base_point_x: float
base_point_y: float
entity_count: int
is_dynamic: bool
attributes: List[str]
@dataclass
class DWGLayer:
"""Represents a DWG layer."""
name: str
color: int
linetype: str
is_on: bool
is_frozen: bool
is_locked: bool
lineweight: float
entity_count: int
class DWGExporter:
"""DWG to Excel converter using DDC DwgExporter CLI."""
def __init__(self, exporter_path: str = "DwgExporter.exe"):
self.exporter = Path(exporter_path)
if not self.exporter.exists():
raise FileNotFoundError(f"DwgExporter not found: {exporter_path}")
def convert(self, dwg_file: str,
export_pdf: bool = False) -> Path:
"""Convert DWG file to Excel."""
dwg_path = Path(dwg_file)
if not dwg_path.exists():
raise FileNotFoundError(f"DWG file not found: {dwg_file}")
cmd = [str(self.exporter), str(dwg_path)]
if export_pdf:
cmd.append("sheets2pdf")
result = subprocess.run(cmd, capture_output=True, text=True)
if result.returncode != 0:
raise RuntimeError(f"Export failed: {result.stderr}")
# Output file is same name with .xlsx extension
return dwg_path.with_suffix('.xlsx')
def batch_convert(self, folder: str,
include_subfolders: bool = True,
export_pdf: bool = False) -> List[Dict[str, Any]]:
"""Convert all DWG files in folder."""
folder_path = Path(folder)
pattern = "**/*.dwg" if include_subfolders else "*.dwg"
results = []
for dwg_file in folder_path.glob(pattern):
try:
output = self.convert(str(dwg_file), export_pdf)
results.append({
'input': str(dwg_file),
'output': str(output),
'status': 'success'
})
print(f"✓ Converted: {dwg_file.name}")
except Exception as e:
results.append({
'input': str(dwg_file),
'output': None,
'status': 'failed',
'error': str(e)
})
print(f"✗ Failed: {dwg_file.name} - {e}")
return results
def read_entities(self, xlsx_file: str) -> pd.DataFrame:
"""Read converted Excel as DataFrame."""
xlsx_path = Path(xlsx_file)
if not xlsx_path.exists():
raise FileNotFoundError(f"Excel file not found: {xlsx_file}")
return pd.read_excel(xlsx_file, sheet_name="Elements")
def get_layers(self, xlsx_file: str) -> pd.DataFrame:
"""Get layer summary from converted file."""
df = self.read_entities(xlsx_file)
if 'Layer' not in df.columns:
raise ValueError("Layer column not found in data")
summary = df.groupby('Layer').agg({
'Handle': 'count'
}).reset_index()
summary.columns = ['Layer', 'Entity_Count']
return summary.sort_values('Entity_Count', ascending=False)
def get_blocks(self, xlsx_file: str) -> pd.DataFrame:
"""Get block reference summary."""
df = self.read_entities(xlsx_file)
# Filter to INSERT entities (block references)
blocks = df[df['EntityType'] == 'INSERT']
if blocks.empty:
return pd.DataFrame(columns=['Block_Name', 'Count'])
summary = blocks.groupby('BlockName').agg({
'Handle': 'count'
}).reset_index()
summary.columns = ['Block_Name', 'Count']
return summary.sort_values('Count', ascending=False)
def get_text_content(self, xlsx_file: str) -> pd.DataFrame:
"""Extract all text content from DWG."""
df = self.read_entities(xlsx_file)
# Filter to text entities
text_types = ['TEXT', 'MTEXT', 'ATTRIB']
texts = df[df['EntityType'].isin(text_types)]
if 'TextContent' in texts.columns:
return texts[['Handle', 'EntityType', 'Layer', 'TextContent']].copy()
return texts[['Handle', 'EntityType', 'Layer']].copy()
def get_entity_statistics(self, xlsx_file: str) -> Dict[str, int]:
"""Get entity type statistics."""
df = self.read_entities(xlsx_file)
if 'EntityType' not in df.columns:
return {}
return df['EntityType'].value_counts().to_dict()
def extract_block_attributes(self, xlsx_file: str,
block_name: str) -> pd.DataFrame:
"""Extract attributes from specific block type."""
df = self.read_entities(xlsx_file)
# Find block references
blocks = df[(df['EntityType'] == 'INSERT') &
(df['BlockName'] == block_name)]
# Find associated attributes
# Attributes typically follow their parent INSERT in handle order
result_data = []
for _, block in blocks.iterrows():
block_handle = block['Handle']
block_data = {
'Block_Handle': block_handle,
'X': block.get('InsertX', 0),
'Y': block.get('InsertY', 0),
'Rotation': block.get('Rotation', 0)
}
# Add any attribute columns
for col in df.columns:
if col.startswith('Attr_'):
block_data[col] = block.get(col)
result_data.append(block_data)
return pd.DataFrame(result_data)
class DWGAnalyzer:
"""Advanced DWG analysis tools."""
def __init__(self, exporter: DWGExporter):
self.exporter = exporter
def analyze_drawing_structure(self, dwg_file: str) -> Dict[str, Any]:
"""Analyze complete drawing structure."""
xlsx = self.exporter.convert(dwg_file)
df = self.exporter.read_entities(str(xlsx))
analysis = {
'file': dwg_file,
'total_entities': len(df),
'layers': self.exporter.get_layers(str(xlsx)).to_dict('records'),
'entity_types': self.exporter.get_entity_statistics(str(xlsx)),
'blocks': self.exporter.get_blocks(str(xlsx)).to_dict('records')
}
# Calculate extents if coordinates available
if 'X' in df.columns and 'Y' in df.columns:
analysis['extents'] = {
'min_x': df['X'].min(),
'max_x': df['X'].max(),
'min_y': df['Y'].min(),
'max_y': df['Y'].max()
}
return analysis
def compare_drawings(self, dwg1: str, dwg2: str) -> Dict[str, Any]:
"""Compare two DWG files."""
xlsx1 = self.exporter.convert(dwg1)
xlsx2 = self.exporter.convert(dwg2)
df1 = self.exporter.read_entities(str(xlsx1))
df2 = self.exporter.read_entities(str(xlsx2))
layers1 = set(df1['Layer'].unique()) if 'Layer' in df1.columns else set()
layers2 = set(df2['Layer'].unique()) if 'Layer' in df2.columns else set()
return {
'file1': dwg1,
'file2': dwg2,
'entity_count_diff': len(df2) - len(df1),
'layers_added': list(layers2 - layers1),
'layers_removed': list(layers1 - layers2),
'common_layers': list(layers1 & layers2)
}
def find_duplicates(self, xlsx_file: str,
tolerance: float = 0.001) -> pd.DataFrame:
"""Find duplicate entities at same location."""
df = self.exporter.read_entities(xlsx_file)
if 'X' not in df.columns or 'Y' not in df.columns:
return pd.DataFrame()
# Round coordinates for grouping
df['X_rounded'] = (df['X'] / tolerance).round() * tolerance
df['Y_rounded'] = (df['Y'] / tolerance).round() * tolerance
# Find duplicates
duplicates = df[df.duplicated(
subset=['EntityType', 'Layer', 'X_rounded', 'Y_rounded'],
keep=False
)]
return duplicates.sort_values(['X_rounded', 'Y_rounded'])
# Convenience functions
def convert_dwg_to_excel(dwg_file: str,
exporter_path: str = "DwgExporter.exe") -> str:
"""Quick conversion of DWG to Excel."""
exporter = DWGExporter(exporter_path)
output = exporter.convert(dwg_file)
return str(output)
def batch_convert_dwg(folder: str,
exporter_path: str = "DwgExporter.exe",
include_subfolders: bool = True) -> List[str]:
"""Batch convert all DWG files in folder."""
exporter = DWGExporter(exporter_path)
results = exporter.batch_convert(folder, include_subfolders)
return [r['output'] for r in results if r['status'] == 'success']
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 505 lines · 42 tokens per session scan A 4b5e5ad7704f
dwg-to-excel is a skill published in the GitHub repository datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction (373 stars, last pushed 8d ago), licensed MIT. It adds 42 tokens to every session and 3,870 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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