# Send Ifc To Excel to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
## Suggested prompts
### New install

```text
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
```
### Upgrade existing

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
```json
{
  "schemaVersion": "1.0",
  "item": {
    "slug": "ifc-to-excel",
    "name": "Ifc To Excel",
    "source": "tencent",
    "type": "skill",
    "category": "开发工具",
    "sourceUrl": "https://clawhub.ai/datadrivenconstruction/ifc-to-excel",
    "canonicalUrl": "https://clawhub.ai/datadrivenconstruction/ifc-to-excel",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadUrl": "/downloads/ifc-to-excel",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=ifc-to-excel",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "packageFormat": "ZIP package",
    "primaryDoc": "SKILL.md",
    "includedAssets": [
      "claw.json",
      "instructions.md",
      "SKILL.md"
    ],
    "downloadMode": "redirect",
    "sourceHealth": {
      "source": "tencent",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-30T16:55:25.780Z",
      "expiresAt": "2026-05-07T16:55:25.780Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network",
        "contentDisposition": "attachment; filename=\"network-1.0.0.zip\"",
        "redirectLocation": null,
        "bodySnippet": null
      },
      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/ifc-to-excel"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    }
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/ifc-to-excel",
    "downloadUrl": "https://openagent3.xyz/downloads/ifc-to-excel",
    "agentUrl": "https://openagent3.xyz/skills/ifc-to-excel/agent",
    "manifestUrl": "https://openagent3.xyz/skills/ifc-to-excel/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/ifc-to-excel/agent.md"
  }
}
```
## Documentation

### Problem Statement

IFC (Industry Foundation Classes) is the open BIM standard, but:

Reading IFC requires specialized software
Property extraction needs programming knowledge
Batch processing is manual and time-consuming
Integration with analytics tools is complex

### Solution

IfcExporter.exe converts IFC files to structured Excel databases, making BIM data accessible for analysis, validation, and reporting.

### Business Value

Open standard - Process any IFC file (2x3, 4x, 4.3)
No licenses - Works offline without BIM software
Data extraction - All properties, quantities, materials
3D geometry - Export to Collada DAE format
Pipeline ready - Integrate with ETL workflows

### CLI Syntax

IfcExporter.exe <input_ifc> [options]

### Supported IFC Versions

VersionSchemaDescriptionIFC2x3MVDMost common exchange formatIFC4ADD1Enhanced propertiesIFC4x1AlignmentInfrastructure supportIFC4x3LatestFull infrastructure

### Output Formats

OutputDescription.xlsxExcel database with elements and properties.daeCollada 3D geometry with matching IDs

### Options

OptionDescriptionbboxInclude element bounding boxes-no-xlsxSkip Excel export-no-colladaSkip 3D geometry export

### Examples

# Basic conversion (XLSX + DAE)
IfcExporter.exe "C:\\Models\\Building.ifc"

# With bounding boxes
IfcExporter.exe "C:\\Models\\Building.ifc" bbox

# Excel only (no 3D geometry)
IfcExporter.exe "C:\\Models\\Building.ifc" -no-collada

# Batch processing
for /R "C:\\IFC_Models" %f in (*.ifc) do IfcExporter.exe "%f" bbox

### Python Integration

import subprocess
import pandas as pd
from pathlib import Path
from typing import List, Optional, Dict, Any, Set
from dataclasses import dataclass, field
from enum import Enum
import json


class IFCVersion(Enum):
    """IFC schema versions."""
    IFC2X3 = "IFC2X3"
    IFC4 = "IFC4"
    IFC4X1 = "IFC4X1"
    IFC4X3 = "IFC4X3"


class IFCEntityType(Enum):
    """Common IFC entity types."""
    IFCWALL = "IfcWall"
    IFCWALLSTANDARDCASE = "IfcWallStandardCase"
    IFCSLAB = "IfcSlab"
    IFCCOLUMN = "IfcColumn"
    IFCBEAM = "IfcBeam"
    IFCDOOR = "IfcDoor"
    IFCWINDOW = "IfcWindow"
    IFCROOF = "IfcRoof"
    IFCSTAIR = "IfcStair"
    IFCRAILING = "IfcRailing"
    IFCFURNISHINGELEMENT = "IfcFurnishingElement"
    IFCSPACE = "IfcSpace"
    IFCBUILDINGSTOREY = "IfcBuildingStorey"
    IFCBUILDING = "IfcBuilding"
    IFCSITE = "IfcSite"


@dataclass
class IFCElement:
    """Represents an IFC element."""
    global_id: str
    ifc_type: str
    name: str
    description: Optional[str]
    object_type: Optional[str]
    level: Optional[str]

    # Quantities
    area: Optional[float] = None
    volume: Optional[float] = None
    length: Optional[float] = None
    height: Optional[float] = None
    width: Optional[float] = None

    # Bounding box (if exported)
    bbox_min_x: Optional[float] = None
    bbox_min_y: Optional[float] = None
    bbox_min_z: Optional[float] = None
    bbox_max_x: Optional[float] = None
    bbox_max_y: Optional[float] = None
    bbox_max_z: Optional[float] = None

    # Properties
    properties: Dict[str, Any] = field(default_factory=dict)
    materials: List[str] = field(default_factory=list)


@dataclass
class IFCProperty:
    """Represents an IFC property."""
    pset_name: str
    property_name: str
    value: Any
    value_type: str


@dataclass
class IFCMaterial:
    """Represents an IFC material."""
    name: str
    category: Optional[str]
    thickness: Optional[float]
    layer_position: Optional[int]


class IFCExporter:
    """IFC to Excel converter using DDC IfcExporter CLI."""

    def __init__(self, exporter_path: str = "IfcExporter.exe"):
        self.exporter = Path(exporter_path)
        if not self.exporter.exists():
            raise FileNotFoundError(f"IfcExporter not found: {exporter_path}")

    def convert(self, ifc_file: str,
                include_bbox: bool = True,
                export_xlsx: bool = True,
                export_collada: bool = True) -> Path:
        """Convert IFC file to Excel."""
        ifc_path = Path(ifc_file)
        if not ifc_path.exists():
            raise FileNotFoundError(f"IFC file not found: {ifc_file}")

        cmd = [str(self.exporter), str(ifc_path)]

        if include_bbox:
            cmd.append("bbox")
        if not export_xlsx:
            cmd.append("-no-xlsx")
        if not export_collada:
            cmd.append("-no-collada")

        result = subprocess.run(cmd, capture_output=True, text=True)

        if result.returncode != 0:
            raise RuntimeError(f"Export failed: {result.stderr}")

        return ifc_path.with_suffix('.xlsx')

    def batch_convert(self, folder: str,
                      include_subfolders: bool = True,
                      include_bbox: bool = True) -> List[Dict[str, Any]]:
        """Convert all IFC files in folder."""
        folder_path = Path(folder)
        pattern = "**/*.ifc" if include_subfolders else "*.ifc"

        results = []
        for ifc_file in folder_path.glob(pattern):
            try:
                output = self.convert(str(ifc_file), include_bbox)
                results.append({
                    'input': str(ifc_file),
                    'output': str(output),
                    'status': 'success'
                })
                print(f"✓ Converted: {ifc_file.name}")
            except Exception as e:
                results.append({
                    'input': str(ifc_file),
                    'output': None,
                    'status': 'failed',
                    'error': str(e)
                })
                print(f"✗ Failed: {ifc_file.name} - {e}")

        return results

    def read_elements(self, xlsx_file: str) -> pd.DataFrame:
        """Read converted Excel as DataFrame."""
        return pd.read_excel(xlsx_file, sheet_name="Elements")

    def get_element_types(self, xlsx_file: str) -> pd.DataFrame:
        """Get element type summary."""
        df = self.read_elements(xlsx_file)

        if 'IfcType' not in df.columns:
            raise ValueError("IfcType column not found")

        summary = df.groupby('IfcType').agg({
            'GlobalId': 'count',
            'Volume': 'sum' if 'Volume' in df.columns else 'count',
            'Area': 'sum' if 'Area' in df.columns else 'count'
        }).reset_index()

        summary.columns = ['IFC_Type', 'Count', 'Total_Volume', 'Total_Area']
        return summary.sort_values('Count', ascending=False)

    def get_levels(self, xlsx_file: str) -> pd.DataFrame:
        """Get building level summary."""
        df = self.read_elements(xlsx_file)

        level_col = None
        for col in ['Level', 'BuildingStorey', 'IfcBuildingStorey']:
            if col in df.columns:
                level_col = col
                break

        if level_col is None:
            return pd.DataFrame(columns=['Level', 'Element_Count'])

        summary = df.groupby(level_col).agg({
            'GlobalId': 'count'
        }).reset_index()
        summary.columns = ['Level', 'Element_Count']
        return summary

    def get_materials(self, xlsx_file: str) -> pd.DataFrame:
        """Get material summary."""
        df = self.read_elements(xlsx_file)

        if 'Material' not in df.columns:
            return pd.DataFrame(columns=['Material', 'Count'])

        summary = df.groupby('Material').agg({
            'GlobalId': 'count'
        }).reset_index()
        summary.columns = ['Material', 'Element_Count']
        return summary.sort_values('Element_Count', ascending=False)

    def get_quantities(self, xlsx_file: str,
                       group_by: str = 'IfcType') -> pd.DataFrame:
        """Get quantity takeoff summary."""
        df = self.read_elements(xlsx_file)

        if group_by not in df.columns:
            raise ValueError(f"Column {group_by} not found")

        agg_dict = {'GlobalId': 'count'}

        # Add numeric columns for aggregation
        numeric_cols = ['Volume', 'Area', 'Length', 'Width', 'Height']
        for col in numeric_cols:
            if col in df.columns:
                agg_dict[col] = 'sum'

        summary = df.groupby(group_by).agg(agg_dict).reset_index()
        return summary

    def filter_by_type(self, xlsx_file: str,
                       ifc_types: List[str]) -> pd.DataFrame:
        """Filter elements by IFC type."""
        df = self.read_elements(xlsx_file)
        return df[df['IfcType'].isin(ifc_types)]

    def get_properties(self, xlsx_file: str,
                       element_id: str) -> Dict[str, Any]:
        """Get all properties for specific element."""
        df = self.read_elements(xlsx_file)
        element = df[df['GlobalId'] == element_id]

        if element.empty:
            return {}

        # Convert row to dictionary, excluding NaN values
        props = element.iloc[0].dropna().to_dict()
        return props

    def validate_ifc_data(self, xlsx_file: str) -> Dict[str, Any]:
        """Validate IFC data quality."""
        df = self.read_elements(xlsx_file)

        validation = {
            'total_elements': len(df),
            'issues': []
        }

        # Check for missing GlobalIds
        if 'GlobalId' in df.columns:
            missing_ids = df['GlobalId'].isna().sum()
            if missing_ids > 0:
                validation['issues'].append(f"{missing_ids} elements missing GlobalId")

        # Check for missing names
        if 'Name' in df.columns:
            missing_names = df['Name'].isna().sum()
            if missing_names > 0:
                validation['issues'].append(f"{missing_names} elements missing Name")

        # Check for zero quantities
        for col in ['Volume', 'Area']:
            if col in df.columns:
                zero_qty = (df[col] == 0).sum()
                if zero_qty > 0:
                    validation['issues'].append(f"{zero_qty} elements with zero {col}")

        # Check for duplicate GlobalIds
        if 'GlobalId' in df.columns:
            duplicates = df['GlobalId'].duplicated().sum()
            if duplicates > 0:
                validation['issues'].append(f"{duplicates} duplicate GlobalIds")

        validation['is_valid'] = len(validation['issues']) == 0
        return validation


class IFCQuantityTakeoff:
    """Quantity takeoff from IFC data."""

    def __init__(self, exporter: IFCExporter):
        self.exporter = exporter

    def generate_qto(self, ifc_file: str) -> Dict[str, pd.DataFrame]:
        """Generate complete quantity takeoff."""
        xlsx = self.exporter.convert(ifc_file, include_bbox=True)
        df = self.exporter.read_elements(str(xlsx))

        qto = {}

        # Walls
        walls = df[df['IfcType'].str.contains('Wall', case=False, na=False)]
        if not walls.empty:
            qto['Walls'] = self._summarize_elements(walls, 'Type Name')

        # Slabs
        slabs = df[df['IfcType'].str.contains('Slab', case=False, na=False)]
        if not slabs.empty:
            qto['Slabs'] = self._summarize_elements(slabs, 'Type Name')

        # Columns
        columns = df[df['IfcType'].str.contains('Column', case=False, na=False)]
        if not columns.empty:
            qto['Columns'] = self._summarize_elements(columns, 'Type Name')

        # Beams
        beams = df[df['IfcType'].str.contains('Beam', case=False, na=False)]
        if not beams.empty:
            qto['Beams'] = self._summarize_elements(beams, 'Type Name')

        # Doors
        doors = df[df['IfcType'].str.contains('Door', case=False, na=False)]
        if not doors.empty:
            qto['Doors'] = self._summarize_elements(doors, 'Type Name')

        # Windows
        windows = df[df['IfcType'].str.contains('Window', case=False, na=False)]
        if not windows.empty:
            qto['Windows'] = self._summarize_elements(windows, 'Type Name')

        return qto

    def _summarize_elements(self, df: pd.DataFrame,
                            group_col: str) -> pd.DataFrame:
        """Summarize elements by grouping column."""
        if group_col not in df.columns:
            group_col = 'IfcType'

        agg_dict = {'GlobalId': 'count'}
        for col in ['Volume', 'Area', 'Length']:
            if col in df.columns:
                agg_dict[col] = 'sum'

        summary = df.groupby(group_col).agg(agg_dict).reset_index()
        summary.rename(columns={'GlobalId': 'Count'}, inplace=True)
        return summary

    def export_to_excel(self, qto: Dict[str, pd.DataFrame],
                        output_file: str):
        """Export QTO to multi-sheet Excel."""
        with pd.ExcelWriter(output_file, engine='openpyxl') as writer:
            for sheet_name, df in qto.items():
                df.to_excel(writer, sheet_name=sheet_name, index=False)


# Convenience functions
def convert_ifc_to_excel(ifc_file: str,
                         exporter_path: str = "IfcExporter.exe") -> str:
    """Quick conversion of IFC to Excel."""
    exporter = IFCExporter(exporter_path)
    output = exporter.convert(ifc_file)
    return str(output)


def get_ifc_summary(xlsx_file: str) -> Dict[str, Any]:
    """Get summary of converted IFC data."""
    df = pd.read_excel(xlsx_file, sheet_name="Elements")

    return {
        'total_elements': len(df),
        'ifc_types': df['IfcType'].nunique() if 'IfcType' in df.columns else 0,
        'levels': df['Level'].nunique() if 'Level' in df.columns else 0,
        'total_volume': df['Volume'].sum() if 'Volume' in df.columns else 0,
        'total_area': df['Area'].sum() if 'Area' in df.columns else 0
    }

### Excel Sheets

SheetContentElementsAll IFC elements with propertiesTypesElement types summaryLevelsBuilding storey dataMaterialsMaterial assignmentsPropertySetsIFC property sets

### Element Columns

ColumnTypeDescriptionGlobalIdstringIFC GUIDIfcTypestringIFC entity typeNamestringElement nameDescriptionstringElement descriptionLevelstringBuilding storeyMaterialstringPrimary materialVolumefloatVolume (m³)AreafloatSurface area (m²)LengthfloatLength (m)HeightfloatHeight (m)WidthfloatWidth (m)

### Quick Start

# Initialize exporter
exporter = IFCExporter("C:/DDC/IfcExporter.exe")

# Convert IFC to Excel
xlsx = exporter.convert("C:/Models/Building.ifc", include_bbox=True)

# Read elements
df = exporter.read_elements(str(xlsx))
print(f"Total elements: {len(df)}")

# Get element types
types = exporter.get_element_types(str(xlsx))
print(types)

# Get quantities by type
qto = exporter.get_quantities(str(xlsx), group_by='IfcType')
print(qto)

### 1. Model Validation

exporter = IFCExporter()
xlsx = exporter.convert("model.ifc")
validation = exporter.validate_ifc_data(str(xlsx))

if not validation['is_valid']:
    print("Issues found:")
    for issue in validation['issues']:
        print(f"  - {issue}")

### 2. Quantity Takeoff

qto_generator = IFCQuantityTakeoff(exporter)
qto = qto_generator.generate_qto("building.ifc")

for category, data in qto.items():
    print(f"\\n{category}:")
    print(data.to_string(index=False))

### 3. Material Schedule

xlsx = exporter.convert("building.ifc")
materials = exporter.get_materials(str(xlsx))
print(materials)

### Integration with DDC Pipeline

# Full pipeline: IFC → Excel → Validation → Cost Estimate
exporter = IFCExporter("C:/DDC/IfcExporter.exe")

# 1. Convert IFC
xlsx = exporter.convert("project.ifc", include_bbox=True)

# 2. Validate data
validation = exporter.validate_ifc_data(str(xlsx))
print(f"Valid: {validation['is_valid']}")

# 3. Generate QTO
qto = IFCQuantityTakeoff(exporter)
quantities = qto.generate_qto("project.ifc")

# 4. Export for cost estimation
qto.export_to_excel(quantities, "project_qto.xlsx")

### Resources

GitHub: cad2data Pipeline
IFC Standard: buildingSMART
DDC Book: Chapter 2.4 - CAD/BIM Data Extraction
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: datadrivenconstruction
- Version: 2.0.0
## Source health
- Status: healthy
- Source download looks usable.
- Yavira can redirect you to the upstream package for this source.
- Health scope: source
- Reason: direct_download_ok
- Checked at: 2026-04-30T16:55:25.780Z
- Expires at: 2026-05-07T16:55:25.780Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/ifc-to-excel)
- [Send to Agent page](https://openagent3.xyz/skills/ifc-to-excel/agent)
- [JSON manifest](https://openagent3.xyz/skills/ifc-to-excel/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/ifc-to-excel/agent.md)
- [Download page](https://openagent3.xyz/downloads/ifc-to-excel)