Automate BIM workflows using visual programming and Python. Create parametric schedules, export data, batch modify elements, and integrate with external data sources.
npx skills add https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill bim-visual-programming-automation
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:
# 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
# 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
# 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()
# 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)
# 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)
# 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)
# 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)
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)
| 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 |
# 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
}
ifc-data-extraction for IFC exportqto-report for advanced quantity reportsn8n-workflow-automation for external integrationComprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Comprehensive technology-agnostic prompt for analyzing and documenting project folder structures. Auto-detects project types (.NET, Java, React, Angular, Python, Node.js, Flutter), generates detailed blueprints with visualization options, naming conventions, file placement patterns, and extension templates for maintaining consistent code organization across diverse technology stacks.
Use when complex problems require systematic step-by-step reasoning with ability to revise thoughts, branch into alternative approaches, or dynamically adjust scope. Ideal for multi-stage analysis, design planning, problem decomposition, or tasks with initially unclear scope.
Multi-agent workflow examples to work together on the OpenServ Platform. Covers agent discovery, multi-agent workspaces, task dependencies, and workflow orchestration using the Platform Client. Read reference.md for the full API reference. Read openserv-agent-sdk and openserv-client for building and running agents.
> Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md.
API design principles and decision-making. REST vs GraphQL vs tRPC selection, response formats, versioning, pagination.
Patterns for automating GitHub workflows with AI assistance, inspired by [Gemini CLI](https://github.com/google-gemini/gemini-cli) and modern DevOps practices.
Groups existing components into logical business domains to plan service-based architecture. Use when asking "which components belong together?", "group these into services", "organize by domain", "component-to-domain mapping", or planning service extraction from an existing codebase. Do NOT use for identifying new domains from scratch (use domain-analysis) or analyzing coupling (use coupling-analysis).
Take datadrivenconstruction/bim-visual-programming-automation from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.