
bim-visual-programming-automation
Automate BIM workflows using visual programming and Python. Create parametric schedules, export data, batch modify elements, and integrate with external data sources.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill bim-visual-programming-automation- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads bim-visual-programming-automation automatically when relevant.
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Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
BIM Visual Programming Automation
Overview
This skill provides visual programming scripts and Python nodes for automating BIM workflows. Extract data, modify elements in batch, generate schedules, and integrate with external systems.
Note: Examples use Autodesk® Revit® and Dynamo™ APIs. Autodesk, Revit, and Dynamo are registered trademarks of Autodesk, Inc.
Key Capabilities:
- Batch element modification
- Data export/import
- Schedule generation
- Parameter management
- External data integration
- Automated QTO
Quick Start (Dynamo Python)
# Dynamo Python Script - Export all walls to Excel
import clr
clr.AddReference('RevitAPI')
clr.AddReference('RevitServices')
from RevitServices.Persistence import DocumentManager
from Autodesk.Revit.DB import FilteredElementCollector, BuiltInCategory
doc = DocumentManager.Instance.CurrentDBDocument
# Get all walls
collector = FilteredElementCollector(doc)
walls = collector.OfCategory(BuiltInCategory.OST_Walls).WhereElementIsNotElementType().ToElements()
# Extract data
wall_data = []
for wall in walls:
wall_data.append({
'id': wall.Id.IntegerValue,
'name': wall.Name,
'length': wall.get_Parameter(BuiltInParameter.CURVE_ELEM_LENGTH).AsDouble() * 0.3048,
'area': wall.get_Parameter(BuiltInParameter.HOST_AREA_COMPUTED).AsDouble() * 0.0929
})
OUT = wall_data
Element Data Extraction
Comprehensive Element Extractor
# Dynamo Python Node - Extract all element data
import clr
clr.AddReference('RevitAPI')
clr.AddReference('RevitServices')
clr.AddReference('RevitNodes')
from RevitServices.Persistence import DocumentManager
from Autodesk.Revit.DB import *
import Revit
clr.ImportExtensions(Revit.Elements)
doc = DocumentManager.Instance.CurrentDBDocument
def get_element_data(element):
"""Extract data from Revit element"""
data = {
'id': element.Id.IntegerValue,
'category': element.Category.Name if element.Category else None,
'name': element.Name,
'level': None,
'parameters': {}
}
# Get level
level_param = element.get_Parameter(BuiltInParameter.SCHEDULE_LEVEL_PARAM)
if level_param:
level_id = level_param.AsElementId()
if level_id.IntegerValue > 0:
level = doc.GetElement(level_id)
data['level'] = level.Name if level else None
# Get all parameters
for param in element.Parameters:
try:
if param.HasValue:
if param.StorageType == StorageType.Double:
data['parameters'][param.Definition.Name] = param.AsDouble()
elif param.StorageType == StorageType.Integer:
data['parameters'][param.Definition.Name] = param.AsInteger()
elif param.StorageType == StorageType.String:
data['parameters'][param.Definition.Name] = param.AsString()
except:
pass
return data
def extract_category(category_enum):
"""Extract all elements of a category"""
collector = FilteredElementCollector(doc)
elements = collector.OfCategory(category_enum).WhereElementIsNotElementType().ToElements()
return [get_element_data(e) for e in elements]
# Extract structural elements
categories = [
BuiltInCategory.OST_Walls,
BuiltInCategory.OST_Floors,
BuiltInCategory.OST_StructuralColumns,
BuiltInCategory.OST_StructuralFraming,
BuiltInCategory.OST_Doors,
BuiltInCategory.OST_Windows
]
all_data = {}
for cat in categories:
cat_name = cat.ToString().replace('OST_', '')
all_data[cat_name] = extract_category(cat)
OUT = all_data
Quantity Take-Off Script
# Dynamo Python - QTO Export
import clr
clr.AddReference('RevitAPI')
clr.AddReference('RevitServices')
from RevitServices.Persistence import DocumentManager
from Autodesk.Revit.DB import *
doc = DocumentManager.Instance.CurrentDBDocument
def get_qto_data():
"""Generate QTO data from model"""
qto = {}
# Walls
walls = FilteredElementCollector(doc).OfCategory(BuiltInCategory.OST_Walls)\
.WhereElementIsNotElementType().ToElements()
wall_qto = {}
for wall in walls:
wall_type = doc.GetElement(wall.GetTypeId())
type_name = wall_type.get_Parameter(BuiltInParameter.ALL_MODEL_TYPE_NAME).AsString()
if type_name not in wall_qto:
wall_qto[type_name] = {'count': 0, 'area': 0, 'length': 0}
wall_qto[type_name]['count'] += 1
area_param = wall.get_Parameter(BuiltInParameter.HOST_AREA_COMPUTED)
if area_param:
wall_qto[type_name]['area'] += area_param.AsDouble() * 0.0929 # sqft to m2
length_param = wall.get_Parameter(BuiltInParameter.CURVE_ELEM_LENGTH)
if length_param:
wall_qto[type_name]['length'] += length_param.AsDouble() * 0.3048 # ft to m
qto['Walls'] = wall_qto
# Floors
floors = FilteredElementCollector(doc).OfCategory(BuiltInCategory.OST_Floors)\
.WhereElementIsNotElementType().ToElements()
floor_qto = {}
for floor in floors:
floor_type = doc.GetElement(floor.GetTypeId())
type_name = floor_type.get_Parameter(BuiltInParameter.ALL_MODEL_TYPE_NAME).AsString()
if type_name not in floor_qto:
floor_qto[type_name] = {'count': 0, 'area': 0, 'volume': 0}
floor_qto[type_name]['count'] += 1
area_param = floor.get_Parameter(BuiltInParameter.HOST_AREA_COMPUTED)
if area_param:
floor_qto[type_name]['area'] += area_param.AsDouble() * 0.0929
vol_param = floor.get_Parameter(BuiltInParameter.HOST_VOLUME_COMPUTED)
if vol_param:
floor_qto[type_name]['volume'] += vol_param.AsDouble() * 0.0283 # cuft to m3
qto['Floors'] = floor_qto
return qto
OUT = get_qto_data()
Batch Modification
Batch Parameter Update
# Dynamo Python - Batch update parameters
import clr
clr.AddReference('RevitAPI')
clr.AddReference('RevitServices')
from RevitServices.Persistence import DocumentManager
from RevitServices.Transactions import TransactionManager
from Autodesk.Revit.DB import *
doc = DocumentManager.Instance.CurrentDBDocument
def batch_update_parameter(elements, param_name, values):
"""Update parameter for multiple elements"""
TransactionManager.Instance.EnsureInTransaction(doc)
results = []
for elem, value in zip(elements, values):
try:
param = elem.LookupParameter(param_name)
if param and not param.IsReadOnly:
if param.StorageType == StorageType.String:
param.Set(str(value))
elif param.StorageType == StorageType.Double:
param.Set(float(value))
elif param.StorageType == StorageType.Integer:
param.Set(int(value))
results.append(True)
else:
results.append(False)
except Exception as e:
results.append(str(e))
TransactionManager.Instance.TransactionTaskDone()
return results
# Input from Dynamo nodes
elements = IN[0] # List of elements
param_name = IN[1] # Parameter name (string)
values = IN[2] # List of values
OUT = batch_update_parameter(elements, param_name, values)
Batch Copy Elements
# Dynamo Python - Copy elements to levels
import clr
clr.AddReference('RevitAPI')
clr.AddReference('RevitServices')
from RevitServices.Persistence import DocumentManager
from RevitServices.Transactions import TransactionManager
from Autodesk.Revit.DB import *
from System.Collections.Generic import List
doc = DocumentManager.Instance.CurrentDBDocument
def copy_to_levels(elements, target_levels):
"""Copy elements to multiple levels"""
TransactionManager.Instance.EnsureInTransaction(doc)
copied = []
element_ids = List[ElementId]([e.Id for e in elements])
for level in target_levels:
# Calculate offset
source_level = doc.GetElement(elements[0].LevelId)
offset = XYZ(0, 0, level.Elevation - source_level.Elevation)
# Copy
new_ids = ElementTransformUtils.CopyElements(
doc, element_ids, offset
)
copied.extend([doc.GetElement(id) for id in new_ids])
TransactionManager.Instance.TransactionTaskDone()
return copied
elements = IN[0]
target_levels = IN[1]
OUT = copy_to_levels(elements, target_levels)
Schedule Generation
Create Custom Schedule
# Dynamo Python - Create view schedule
import clr
clr.AddReference('RevitAPI')
clr.AddReference('RevitServices')
from RevitServices.Persistence import DocumentManager
from RevitServices.Transactions import TransactionManager
from Autodesk.Revit.DB import *
doc = DocumentManager.Instance.CurrentDBDocument
def create_wall_schedule(schedule_name):
"""Create a wall schedule with QTO fields"""
TransactionManager.Instance.EnsureInTransaction(doc)
# Create schedule
schedule = ViewSchedule.CreateSchedule(
doc,
ElementId(BuiltInCategory.OST_Walls)
)
schedule.Name = schedule_name
# Add fields
definition = schedule.Definition
schedulable = definition.GetSchedulableFields()
# Find and add specific fields
field_names = ['Type', 'Level', 'Length', 'Area', 'Volume']
for sf in schedulable:
if sf.GetName(doc) in field_names:
definition.AddField(sf)
# Add sorting/grouping
type_field = None
for field in definition.GetFieldOrder():
if definition.GetField(field).GetName() == 'Type':
type_field = field
break
if type_field:
sorting = ScheduleSortGroupField(type_field, ScheduleSortOrder.Ascending)
sorting.ShowHeader = True
sorting.ShowFooter = True
definition.AddSortGroupField(sorting)
TransactionManager.Instance.TransactionTaskDone()
return schedule
schedule_name = IN[0]
OUT = create_wall_schedule(schedule_name)
External Data Integration
Import Data from Excel
# Dynamo Python - Import Excel and update Revit
import clr
clr.AddReference('RevitAPI')
clr.AddReference('RevitServices')
from RevitServices.Persistence import DocumentManager
from RevitServices.Transactions import TransactionManager
from Autodesk.Revit.DB import *
# Requires Excel data as input from Dynamo Excel nodes
doc = DocumentManager.Instance.CurrentDBDocument
def update_from_excel(excel_data, id_column, param_columns):
"""Update Revit elements from Excel data"""
TransactionManager.Instance.EnsureInTransaction(doc)
results = []
for row in excel_data:
try:
# Get element by ID
elem_id = ElementId(int(row[id_column]))
element = doc.GetElement(elem_id)
if element:
row_result = {'id': elem_id.IntegerValue, 'updates': {}}
for col_name, col_index in param_columns.items():
param = element.LookupParameter(col_name)
if param and not param.IsReadOnly:
value = row[col_index]
if param.StorageType == StorageType.String:
param.Set(str(value))
elif param.StorageType == StorageType.Double:
param.Set(float(value))
row_result['updates'][col_name] = value
results.append(row_result)
except Exception as e:
results.append({'error': str(e)})
TransactionManager.Instance.TransactionTaskDone()
return results
excel_data = IN[0] # 2D list from Excel
id_column = IN[1] # Column index for element ID
param_columns = IN[2] # Dict: param_name -> column_index
OUT = update_from_excel(excel_data, id_column, param_columns)
Dynamo Package Workflow
Full QTO Pipeline (Dynamo Graph Nodes)
1. Categories (Input)
|
2. All Elements of Category (Revit)
|
3. Element.GetParameterValueByName (Multiple parameters)
|
4. Python Script (Process and calculate)
|
5. List.Transpose
|
6. Data.ExportExcel
|
7. File Path (Output)
Quick Reference
| Task | Method | Performance |
|---|---|---|
| Get Elements | FilteredElementCollector | Fast |
| Get Parameter | element.LookupParameter() | Fast |
| Set Parameter | TransactionManager required | Moderate |
| Copy Elements | ElementTransformUtils | Moderate |
| Create Views | ViewSchedule.CreateSchedule | Slow |
| Delete Elements | Document.Delete | Fast |
Common Parameter Names
# Built-in parameters for quantities
QUANTITY_PARAMS = {
'Length': BuiltInParameter.CURVE_ELEM_LENGTH,
'Area': BuiltInParameter.HOST_AREA_COMPUTED,
'Volume': BuiltInParameter.HOST_VOLUME_COMPUTED,
'Height': BuiltInParameter.WALL_USER_HEIGHT_PARAM,
'Width': BuiltInParameter.DOOR_WIDTH,
'Level': BuiltInParameter.SCHEDULE_LEVEL_PARAM
}
# Unit conversion (Imperial to Metric)
CONVERSIONS = {
'feet_to_meters': 0.3048,
'sqft_to_sqm': 0.0929,
'cuft_to_cum': 0.0283
}
Resources
- Dynamo Primer: https://primer.dynamobim.org
- Revit API Docs: https://www.revitapidocs.com
- DDC Website: https://datadrivenconstruction.io
Next Steps
- See
ifc-data-extractionfor IFC export - See
qto-reportfor advanced quantity reports - See
n8n-workflow-automationfor external integration
FAQ
What does the bim-visual-programming-automation skill do?
Automate BIM workflows using visual programming and Python. Create parametric schedules, export data, batch modify elements, and integrate with external data sources.
How do I install bim-visual-programming-automation?
Run npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill bim-visual-programming-automation in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/bim-visual-programming-automation/ (personal) or .claude/skills/bim-visual-programming-automation/ (project).
Which AI agents can use bim-visual-programming-automation?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is bim-visual-programming-automation safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains bim-visual-programming-automation?
It is published by datadrivenconstruction in datadrivenconstruction/ddc_skills_for_ai_agents_in_construction. It has 114 recorded installs.
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