Creator · datadrivenconstruction
Last updated · Sep 6, 2026
Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting.
Creator · datadrivenconstruction
Last updated · Sep 6, 2026
Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting.
Creator · datadrivenconstruction
Last updated · Sep 6, 2026
Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting.
Creator · datadrivenconstruction
Last updated · Sep 6, 2026
Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting.
Sandbox only
Install targets
Codex install prompt
Install the "batch-cad-converter" agent skill from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/CAD-Converters/batch-cad-converter. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"datadrivenconstruction-batch-cad-converter","task":"Install batch-cad-converter","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converter
Maintenance
fresh
16d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
305
72/100 Quality · 68/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · The SKILL.md excerpt is truncated, but the available content is sufficient to understand the skill's purpose and workflow.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
305 GitHub stars
Repo activity
305 stars, 80 forks
Maintenance
16d since push
License
MIT
Install
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converter
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converterDo not use when
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20batch-cad-converter%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20batch-cad-converter%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/datadrivenconstruction-batch-cad-converter/install
Agent should check
Copy prompt
Task: Use batch-cad-converter in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20batch-cad-converter%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/datadrivenconstruction-batch-cad-converter/install
Install command: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converter
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/datadrivenconstruction-batch-cad-converter/install
LLM text format
/api/skills/datadrivenconstruction-batch-cad-converter/install?format=text
Find alternatives
/api/skills/search?q=batch-cad-converter&limit=3
Agent prompt
Use batch-cad-converter for this task. Review https://www.openagentskill.com/api/skills/datadrivenconstruction-batch-cad-converter/install, then install with: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converterRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/datadrivenconstruction-batch-cad-converter
LLM text
/api/registry/manifest/datadrivenconstruction-batch-cad-converter?format=text
Install alias
/api/registry/install/datadrivenconstruction-batch-cad-converter
Recommend
/api/registry/recommend?task=Use%20batch-cad-converter%20in%20an%20agent%20workflow&limit=3
Agent fit
Browser automation
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Browser automation
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO305 GitHub stars
Stars/forks activity
INFO305 stars, 80 forks; issue activity unavailable in current metadata
Recent maintenance
PASS16d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Workflow fit
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Run multimodal agents that operate desktop interfaces
Connect agents to hundreds of workflow automations
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--- name: "batch-cad-converter" description: "Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting." homepage: "https://datadrivenconstruction.io" metadata: {"openclaw":{"emoji":"🔄","os":["win32"],"homepage":"https://datadrivenconstruction.io","requires":{"bins":["python3"],"anyBins":["RvtExporter","DwgExporter","DgnExporter","RVT2IFCconverter"]}}} ---
# Batch CAD/BIM Converter
## Business Case
### Problem Statement Large projects and archives contain hundreds or thousands of CAD/BIM files: - Manual conversion is tedious and error-prone - Different formats require different converters - Progress tracking is needed for long operations - Error handling is critical for large batches
### Solution Unified batch converter handling all supported formats with progress tracking, error recovery, and consolidated reporting.
### Business Value - **Multi-format** - Revit, IFC, DWG, DGN in one workflow - **Error recovery** - Continue on failures - **Progress tracking** - Monitor large batches - **Reporting** - Consolidated conversion results
## Python Implementation
```python import subprocess from pathlib import Path from typing import List, Optional, Dict, Any, Callable from dataclasses import dataclass, field from datetime import datetime import time import json from enum import Enum from concurrent.futures import ThreadPoolExecutor, as_completed
class CADFormat(Enum): """Supported CAD/BIM formats.""" REVIT = (".rvt", ".rfa") IFC = (".ifc",) DWG = (".dwg",) DGN = (".dgn",)
class ConversionStatus(Enum): """Status of conversion operation.""" PENDING = "pending" CONVERTING = "converting" SUCCESS = "success" FAILED = "failed" SKIPPED = "skipped"
@dataclass class ConversionResult: """Result of single file conversion.""" input_file: str output_file: Optional[str] format: str status: ConversionStatus start_time: datetime end_time: Optional[datetime] duration_seconds: float error_message: Optional[str] = None file_size_kb: float = 0
@dataclass class BatchResult: """Result of batch conversion.""" total_files: int successful: int failed: int skipped: int total_duration: float results: List[ConversionResult] start_time: datetime end_time: datetime
class BatchCADConverter: """Batch convert multiple CAD/BIM files."""
# Default converter paths DEFAULT_CONVERTERS = { 'revit': 'RvtExporter.exe', 'ifc': 'IfcExporter.exe', 'dwg': 'DwgExporter.exe', 'dgn': 'DgnExporter.exe' }
def __init__(self, converter_dir: str = ".", converters: Dict[str, str] = None): self.converter_dir = Path(converter_dir) self.converters = converters or self.DEFAULT_CONVERTERS self.results: List[ConversionResult] = [] self.progress_callback: Optional[Callable] = None
def set_progress_callback(self, callback: Callable[[int, int, str], None]): """Set callback for progress updates.""" self.progress_callback = callback
def _get_format(self, file_path: Path) -> Optional[str]: """Detect CAD format from extension.""" ext = file_path.suffix.lower()
for format_name, extensions in [ ('revit', ('.rvt', '.rfa')), ('ifc', ('.ifc',)), ('dwg', ('.dwg',)), ('dgn', ('.dgn',)) ]: if ext in extensions: return format_name
return None
def _get_converter(self, format_name: str) -> Optional[Path]: """Get converter path for format.""" if format_name not in self.converters: return None
converter = self.converter_dir / self.converters[format_name] if converter.exists(): return converter
# Try in system PATH return Path(self.converters[format_name])
def convert_file(self, input_file: str, output_dir: Optional[str] = None, options: List[str] = None) -> ConversionResult: """Convert single file."""
input_path = Path(input_file) start_time = datetime.now()
# Detect format format_name = self._get_format(input_path) if not format_name: return ConversionResult( input_file=input_file, output_file=None, format='unknown', status=ConversionStatus.SKIPPED, start_time=start_time, end_time=datetime.now(), duration_seconds=0, error_message="Unsupported format" )
# Get converter converter = self._get_converter(format_name) if not converter: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=datetime.now(), duration_seconds=0, error_message=f"Converter not found for {format_name}" )
# Build command cmd = [str(converter), str(input_path)] if options: cmd.extend(options)
# Execute try: result = subprocess.run(cmd, capture_output=True, text=True, timeout=3600) end_time = datetime.now() duration = (end_time - start_time).total_seconds()
# Determine output file output_file = input_path.with_suffix('.xlsx') if output_dir: output_file = Path(output_dir) / output_file.name
if result.returncode == 0 and output_file.exists(): return ConversionResult( input_file=input_file, output_file=str(output_file), format=format_name, status=ConversionStatus.SUCCESS, start_time=start_time, end_time=end_time, duration_seconds=duration, file_size_kb=output_file.stat().st_size / 1024 ) else: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=end_time, duration_seconds=duration, error_message=result.stderr or "Conversion failed" )
except subprocess.TimeoutExpired: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=datetime.now(), duration_seconds=3600, error_message="Timeout exceeded (1 hour)" )
except Exception as e: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=datetime.now(), duration_seconds=0, error_message=str(e) )
def batch_convert(self, input_folder: str, output_folder: Optional[str] = None, include_subfolders: bool = True, formats: List[str] = None, options: Dict[str, List[str]] = None, parallel: bool = False, max_workers: int = 4) -> BatchResult: """Convert all files in folder."""
start_time = datetime.now() input_path = Path(input_folder)
# Find all supported files files = [] pattern = "**/*" if include_subfolders else "*"
for ext in ['.rvt', '.rfa', '.ifc', '.dwg', '.dgn']: files.extend(input_path.glob(f"{pattern}{ext}"))
# Filter by format if specified if formats: files = [f for f in files if self._get_format(f) in formats]
total_files = len(files) self.results = []
# Create output directory if output_folder: Path(output_folder).mkdir(parents=True, exist_ok=True)
# Process files if parallel and total_files > 1: self._convert_parallel(files, output_folder, options, max_workers) else: self._convert_sequential(files, output_folder, options)
end_time = datetime.now()
# Calculate statistics successful = sum(1 for r in self.results if r.status == ConversionStatus.SUCCESS) failed = sum(1 for r in self.results if r.status == ConversionStatus.FAILED) skipped = sum(1 for r in self.results if r.status == ConversionStatus.SKIPPED)
return BatchResult( total_files=total_files, successful=successful, failed=failed, skipped=skipped, total_duration=(end_time - start_time).total_seconds(), results=self.results, start_time=start_time, end_time=end_time )
def _convert_sequential(self, files: List[Path], output_folder: Optional[str], options: Dict[str, List[str]]): """Convert files sequentially."""
total = len(files) for i, file_path in enumerate(files, 1): if self.progress_callback: self.progress_callback(i, total, str(file_path))
format_name = self._get_format(file_path) format_options = options.get(format_name, []) if options else []
result = self.convert_file(str(file_path), output_folder, format_options) self.results.append(result)
status_symbol = "✓" if result.status == ConversionStatus.SUCCESS else "✗" print(f"[{i}/{total}] {status_symbol} {file_path.name}")
def _convert_parallel(self, files: List[Path], output_folder: Optional[str], options: Dict[str, List[str]], max_workers: int): """Convert files in parallel."""
total = len(files)
with ThreadPoolExecutor(max_workers=max_workers) as executor: futures = {}
for file_path in files: format_name = self._get_format(file_path) format_options = options.get(format_name, []) if options else [] future = executor.submit(self.convert_file, str(file_path), output_folder, format_options) futures[future] = file_path
completed = 0 for future in as_completed(futures): completed += 1 result = future.result() self.results.append(result)
if self.progress_callback: self.progress_callback(completed, total, str(futures[future]))
def generate_report(self, batch_result: BatchResult, output_path: str = None) -> str: """Generate conversion report."""
report = { 'summary': { 'total_files': batch_result.total_files, 'successful': batch_result.successful, 'failed': batch_result.failed, 'skipped': batch_result.skipped, 'success_rate': round(batch_result.successful / batch_result.total_files * 100, 1) if batch_result.total_files > 0 else 0, 'total_duration_seconds': round(batch_result.total_duration, 2), 'start_time': batch_result.start_time.isoforma
Source provenance
Decision snapshot
recent repository activity
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for batch-cad-converter, ready for a manual X post.
batch-cad-converter: Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error han... 305 stars https://www.openagentskill.com/skills/datadrivenconstruction-batch-cad-converter?ref=x
Listing + install path for batch-cad-converter: https://www.openagentskill.com/skills/datadrivenconstruction-batch-cad-converter?ref=x Install: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --...
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
This Registry indexed listing is attributed to datadrivenconstruction but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/datadrivenconstruction-batch-cad-converter?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/datadrivenconstruction-batch-cad-converter?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/datadrivenconstruction-batch-cad-converter/audit)
[](https://www.openagentskill.com/skills/datadrivenconstruction-batch-cad-converter?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)datadrivenconstruction
@datadrivenconstruction
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Install targets
Codex install prompt
Install the "batch-cad-converter" agent skill from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/CAD-Converters/batch-cad-converter. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"datadrivenconstruction-batch-cad-converter","task":"Install batch-cad-converter","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converter
Maintenance
fresh
16d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
305
72/100 Quality · 68/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · The SKILL.md excerpt is truncated, but the available content is sufficient to understand the skill's purpose and workflow.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
305 GitHub stars
Repo activity
305 stars, 80 forks
Maintenance
16d since push
License
MIT
Install
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converter
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converterDo not use when
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20batch-cad-converter%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20batch-cad-converter%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/datadrivenconstruction-batch-cad-converter/install
Agent should check
Copy prompt
Task: Use batch-cad-converter in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20batch-cad-converter%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/datadrivenconstruction-batch-cad-converter/install
Install command: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converter
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/datadrivenconstruction-batch-cad-converter/install
LLM text format
/api/skills/datadrivenconstruction-batch-cad-converter/install?format=text
Find alternatives
/api/skills/search?q=batch-cad-converter&limit=3
Agent prompt
Use batch-cad-converter for this task. Review https://www.openagentskill.com/api/skills/datadrivenconstruction-batch-cad-converter/install, then install with: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converterRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/datadrivenconstruction-batch-cad-converter
LLM text
/api/registry/manifest/datadrivenconstruction-batch-cad-converter?format=text
Install alias
/api/registry/install/datadrivenconstruction-batch-cad-converter
Recommend
/api/registry/recommend?task=Use%20batch-cad-converter%20in%20an%20agent%20workflow&limit=3
Agent fit
Browser automation
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Browser automation
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO305 GitHub stars
Stars/forks activity
INFO305 stars, 80 forks; issue activity unavailable in current metadata
Recent maintenance
PASS16d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Workflow fit
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Run multimodal agents that operate desktop interfaces
Connect agents to hundreds of workflow automations
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Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at
--- name: "batch-cad-converter" description: "Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting." homepage: "https://datadrivenconstruction.io" metadata: {"openclaw":{"emoji":"🔄","os":["win32"],"homepage":"https://datadrivenconstruction.io","requires":{"bins":["python3"],"anyBins":["RvtExporter","DwgExporter","DgnExporter","RVT2IFCconverter"]}}} ---
# Batch CAD/BIM Converter
## Business Case
### Problem Statement Large projects and archives contain hundreds or thousands of CAD/BIM files: - Manual conversion is tedious and error-prone - Different formats require different converters - Progress tracking is needed for long operations - Error handling is critical for large batches
### Solution Unified batch converter handling all supported formats with progress tracking, error recovery, and consolidated reporting.
### Business Value - **Multi-format** - Revit, IFC, DWG, DGN in one workflow - **Error recovery** - Continue on failures - **Progress tracking** - Monitor large batches - **Reporting** - Consolidated conversion results
## Python Implementation
```python import subprocess from pathlib import Path from typing import List, Optional, Dict, Any, Callable from dataclasses import dataclass, field from datetime import datetime import time import json from enum import Enum from concurrent.futures import ThreadPoolExecutor, as_completed
class CADFormat(Enum): """Supported CAD/BIM formats.""" REVIT = (".rvt", ".rfa") IFC = (".ifc",) DWG = (".dwg",) DGN = (".dgn",)
class ConversionStatus(Enum): """Status of conversion operation.""" PENDING = "pending" CONVERTING = "converting" SUCCESS = "success" FAILED = "failed" SKIPPED = "skipped"
@dataclass class ConversionResult: """Result of single file conversion.""" input_file: str output_file: Optional[str] format: str status: ConversionStatus start_time: datetime end_time: Optional[datetime] duration_seconds: float error_message: Optional[str] = None file_size_kb: float = 0
@dataclass class BatchResult: """Result of batch conversion.""" total_files: int successful: int failed: int skipped: int total_duration: float results: List[ConversionResult] start_time: datetime end_time: datetime
class BatchCADConverter: """Batch convert multiple CAD/BIM files."""
# Default converter paths DEFAULT_CONVERTERS = { 'revit': 'RvtExporter.exe', 'ifc': 'IfcExporter.exe', 'dwg': 'DwgExporter.exe', 'dgn': 'DgnExporter.exe' }
def __init__(self, converter_dir: str = ".", converters: Dict[str, str] = None): self.converter_dir = Path(converter_dir) self.converters = converters or self.DEFAULT_CONVERTERS self.results: List[ConversionResult] = [] self.progress_callback: Optional[Callable] = None
def set_progress_callback(self, callback: Callable[[int, int, str], None]): """Set callback for progress updates.""" self.progress_callback = callback
def _get_format(self, file_path: Path) -> Optional[str]: """Detect CAD format from extension.""" ext = file_path.suffix.lower()
for format_name, extensions in [ ('revit', ('.rvt', '.rfa')), ('ifc', ('.ifc',)), ('dwg', ('.dwg',)), ('dgn', ('.dgn',)) ]: if ext in extensions: return format_name
return None
def _get_converter(self, format_name: str) -> Optional[Path]: """Get converter path for format.""" if format_name not in self.converters: return None
converter = self.converter_dir / self.converters[format_name] if converter.exists(): return converter
# Try in system PATH return Path(self.converters[format_name])
def convert_file(self, input_file: str, output_dir: Optional[str] = None, options: List[str] = None) -> ConversionResult: """Convert single file."""
input_path = Path(input_file) start_time = datetime.now()
# Detect format format_name = self._get_format(input_path) if not format_name: return ConversionResult( input_file=input_file, output_file=None, format='unknown', status=ConversionStatus.SKIPPED, start_time=start_time, end_time=datetime.now(), duration_seconds=0, error_message="Unsupported format" )
# Get converter converter = self._get_converter(format_name) if not converter: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=datetime.now(), duration_seconds=0, error_message=f"Converter not found for {format_name}" )
# Build command cmd = [str(converter), str(input_path)] if options: cmd.extend(options)
# Execute try: result = subprocess.run(cmd, capture_output=True, text=True, timeout=3600) end_time = datetime.now() duration = (end_time - start_time).total_seconds()
# Determine output file output_file = input_path.with_suffix('.xlsx') if output_dir: output_file = Path(output_dir) / output_file.name
if result.returncode == 0 and output_file.exists(): return ConversionResult( input_file=input_file, output_file=str(output_file), format=format_name, status=ConversionStatus.SUCCESS, start_time=start_time, end_time=end_time, duration_seconds=duration, file_size_kb=output_file.stat().st_size / 1024 ) else: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=end_time, duration_seconds=duration, error_message=result.stderr or "Conversion failed" )
except subprocess.TimeoutExpired: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=datetime.now(), duration_seconds=3600, error_message="Timeout exceeded (1 hour)" )
except Exception as e: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=datetime.now(), duration_seconds=0, error_message=str(e) )
def batch_convert(self, input_folder: str, output_folder: Optional[str] = None, include_subfolders: bool = True, formats: List[str] = None, options: Dict[str, List[str]] = None, parallel: bool = False, max_workers: int = 4) -> BatchResult: """Convert all files in folder."""
start_time = datetime.now() input_path = Path(input_folder)
# Find all supported files files = [] pattern = "**/*" if include_subfolders else "*"
for ext in ['.rvt', '.rfa', '.ifc', '.dwg', '.dgn']: files.extend(input_path.glob(f"{pattern}{ext}"))
# Filter by format if specified if formats: files = [f for f in files if self._get_format(f) in formats]
total_files = len(files) self.results = []
# Create output directory if output_folder: Path(output_folder).mkdir(parents=True, exist_ok=True)
# Process files if parallel and total_files > 1: self._convert_parallel(files, output_folder, options, max_workers) else: self._convert_sequential(files, output_folder, options)
end_time = datetime.now()
# Calculate statistics successful = sum(1 for r in self.results if r.status == ConversionStatus.SUCCESS) failed = sum(1 for r in self.results if r.status == ConversionStatus.FAILED) skipped = sum(1 for r in self.results if r.status == ConversionStatus.SKIPPED)
return BatchResult( total_files=total_files, successful=successful, failed=failed, skipped=skipped, total_duration=(end_time - start_time).total_seconds(), results=self.results, start_time=start_time, end_time=end_time )
def _convert_sequential(self, files: List[Path], output_folder: Optional[str], options: Dict[str, List[str]]): """Convert files sequentially."""
total = len(files) for i, file_path in enumerate(files, 1): if self.progress_callback: self.progress_callback(i, total, str(file_path))
format_name = self._get_format(file_path) format_options = options.get(format_name, []) if options else []
result = self.convert_file(str(file_path), output_folder, format_options) self.results.append(result)
status_symbol = "✓" if result.status == ConversionStatus.SUCCESS else "✗" print(f"[{i}/{total}] {status_symbol} {file_path.name}")
def _convert_parallel(self, files: List[Path], output_folder: Optional[str], options: Dict[str, List[str]], max_workers: int): """Convert files in parallel."""
total = len(files)
with ThreadPoolExecutor(max_workers=max_workers) as executor: futures = {}
for file_path in files: format_name = self._get_format(file_path) format_options = options.get(format_name, []) if options else [] future = executor.submit(self.convert_file, str(file_path), output_folder, format_options) futures[future] = file_path
completed = 0 for future in as_completed(futures): completed += 1 result = future.result() self.results.append(result)
if self.progress_callback: self.progress_callback(completed, total, str(futures[future]))
def generate_report(self, batch_result: BatchResult, output_path: str = None) -> str: """Generate conversion report."""
report = { 'summary': { 'total_files': batch_result.total_files, 'successful': batch_result.successful, 'failed': batch_result.failed, 'skipped': batch_result.skipped, 'success_rate': round(batch_result.successful / batch_result.total_files * 100, 1) if batch_result.total_files > 0 else 0, 'total_duration_seconds': round(batch_result.total_duration, 2), 'start_time': batch_result.start_time.isoforma
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batch-cad-converter: Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error han... 305 stars https://www.openagentskill.com/skills/datadrivenconstruction-batch-cad-converter?ref=x
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Install the "batch-cad-converter" agent skill from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/CAD-Converters/batch-cad-converter. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"datadrivenconstruction-batch-cad-converter","task":"Install batch-cad-converter","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
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npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converter
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npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converterDo not use when
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Run multimodal agents that operate desktop interfaces
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利用AI大模型,一键生成高清短视频 Generate short videos with one click using AI LLM.
Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at
--- name: "batch-cad-converter" description: "Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting." homepage: "https://datadrivenconstruction.io" metadata: {"openclaw":{"emoji":"🔄","os":["win32"],"homepage":"https://datadrivenconstruction.io","requires":{"bins":["python3"],"anyBins":["RvtExporter","DwgExporter","DgnExporter","RVT2IFCconverter"]}}} ---
# Batch CAD/BIM Converter
## Business Case
### Problem Statement Large projects and archives contain hundreds or thousands of CAD/BIM files: - Manual conversion is tedious and error-prone - Different formats require different converters - Progress tracking is needed for long operations - Error handling is critical for large batches
### Solution Unified batch converter handling all supported formats with progress tracking, error recovery, and consolidated reporting.
### Business Value - **Multi-format** - Revit, IFC, DWG, DGN in one workflow - **Error recovery** - Continue on failures - **Progress tracking** - Monitor large batches - **Reporting** - Consolidated conversion results
## Python Implementation
```python import subprocess from pathlib import Path from typing import List, Optional, Dict, Any, Callable from dataclasses import dataclass, field from datetime import datetime import time import json from enum import Enum from concurrent.futures import ThreadPoolExecutor, as_completed
class CADFormat(Enum): """Supported CAD/BIM formats.""" REVIT = (".rvt", ".rfa") IFC = (".ifc",) DWG = (".dwg",) DGN = (".dgn",)
class ConversionStatus(Enum): """Status of conversion operation.""" PENDING = "pending" CONVERTING = "converting" SUCCESS = "success" FAILED = "failed" SKIPPED = "skipped"
@dataclass class ConversionResult: """Result of single file conversion.""" input_file: str output_file: Optional[str] format: str status: ConversionStatus start_time: datetime end_time: Optional[datetime] duration_seconds: float error_message: Optional[str] = None file_size_kb: float = 0
@dataclass class BatchResult: """Result of batch conversion.""" total_files: int successful: int failed: int skipped: int total_duration: float results: List[ConversionResult] start_time: datetime end_time: datetime
class BatchCADConverter: """Batch convert multiple CAD/BIM files."""
# Default converter paths DEFAULT_CONVERTERS = { 'revit': 'RvtExporter.exe', 'ifc': 'IfcExporter.exe', 'dwg': 'DwgExporter.exe', 'dgn': 'DgnExporter.exe' }
def __init__(self, converter_dir: str = ".", converters: Dict[str, str] = None): self.converter_dir = Path(converter_dir) self.converters = converters or self.DEFAULT_CONVERTERS self.results: List[ConversionResult] = [] self.progress_callback: Optional[Callable] = None
def set_progress_callback(self, callback: Callable[[int, int, str], None]): """Set callback for progress updates.""" self.progress_callback = callback
def _get_format(self, file_path: Path) -> Optional[str]: """Detect CAD format from extension.""" ext = file_path.suffix.lower()
for format_name, extensions in [ ('revit', ('.rvt', '.rfa')), ('ifc', ('.ifc',)), ('dwg', ('.dwg',)), ('dgn', ('.dgn',)) ]: if ext in extensions: return format_name
return None
def _get_converter(self, format_name: str) -> Optional[Path]: """Get converter path for format.""" if format_name not in self.converters: return None
converter = self.converter_dir / self.converters[format_name] if converter.exists(): return converter
# Try in system PATH return Path(self.converters[format_name])
def convert_file(self, input_file: str, output_dir: Optional[str] = None, options: List[str] = None) -> ConversionResult: """Convert single file."""
input_path = Path(input_file) start_time = datetime.now()
# Detect format format_name = self._get_format(input_path) if not format_name: return ConversionResult( input_file=input_file, output_file=None, format='unknown', status=ConversionStatus.SKIPPED, start_time=start_time, end_time=datetime.now(), duration_seconds=0, error_message="Unsupported format" )
# Get converter converter = self._get_converter(format_name) if not converter: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=datetime.now(), duration_seconds=0, error_message=f"Converter not found for {format_name}" )
# Build command cmd = [str(converter), str(input_path)] if options: cmd.extend(options)
# Execute try: result = subprocess.run(cmd, capture_output=True, text=True, timeout=3600) end_time = datetime.now() duration = (end_time - start_time).total_seconds()
# Determine output file output_file = input_path.with_suffix('.xlsx') if output_dir: output_file = Path(output_dir) / output_file.name
if result.returncode == 0 and output_file.exists(): return ConversionResult( input_file=input_file, output_file=str(output_file), format=format_name, status=ConversionStatus.SUCCESS, start_time=start_time, end_time=end_time, duration_seconds=duration, file_size_kb=output_file.stat().st_size / 1024 ) else: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=end_time, duration_seconds=duration, error_message=result.stderr or "Conversion failed" )
except subprocess.TimeoutExpired: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=datetime.now(), duration_seconds=3600, error_message="Timeout exceeded (1 hour)" )
except Exception as e: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=datetime.now(), duration_seconds=0, error_message=str(e) )
def batch_convert(self, input_folder: str, output_folder: Optional[str] = None, include_subfolders: bool = True, formats: List[str] = None, options: Dict[str, List[str]] = None, parallel: bool = False, max_workers: int = 4) -> BatchResult: """Convert all files in folder."""
start_time = datetime.now() input_path = Path(input_folder)
# Find all supported files files = [] pattern = "**/*" if include_subfolders else "*"
for ext in ['.rvt', '.rfa', '.ifc', '.dwg', '.dgn']: files.extend(input_path.glob(f"{pattern}{ext}"))
# Filter by format if specified if formats: files = [f for f in files if self._get_format(f) in formats]
total_files = len(files) self.results = []
# Create output directory if output_folder: Path(output_folder).mkdir(parents=True, exist_ok=True)
# Process files if parallel and total_files > 1: self._convert_parallel(files, output_folder, options, max_workers) else: self._convert_sequential(files, output_folder, options)
end_time = datetime.now()
# Calculate statistics successful = sum(1 for r in self.results if r.status == ConversionStatus.SUCCESS) failed = sum(1 for r in self.results if r.status == ConversionStatus.FAILED) skipped = sum(1 for r in self.results if r.status == ConversionStatus.SKIPPED)
return BatchResult( total_files=total_files, successful=successful, failed=failed, skipped=skipped, total_duration=(end_time - start_time).total_seconds(), results=self.results, start_time=start_time, end_time=end_time )
def _convert_sequential(self, files: List[Path], output_folder: Optional[str], options: Dict[str, List[str]]): """Convert files sequentially."""
total = len(files) for i, file_path in enumerate(files, 1): if self.progress_callback: self.progress_callback(i, total, str(file_path))
format_name = self._get_format(file_path) format_options = options.get(format_name, []) if options else []
result = self.convert_file(str(file_path), output_folder, format_options) self.results.append(result)
status_symbol = "✓" if result.status == ConversionStatus.SUCCESS else "✗" print(f"[{i}/{total}] {status_symbol} {file_path.name}")
def _convert_parallel(self, files: List[Path], output_folder: Optional[str], options: Dict[str, List[str]], max_workers: int): """Convert files in parallel."""
total = len(files)
with ThreadPoolExecutor(max_workers=max_workers) as executor: futures = {}
for file_path in files: format_name = self._get_format(file_path) format_options = options.get(format_name, []) if options else [] future = executor.submit(self.convert_file, str(file_path), output_folder, format_options) futures[future] = file_path
completed = 0 for future in as_completed(futures): completed += 1 result = future.result() self.results.append(result)
if self.progress_callback: self.progress_callback(completed, total, str(futures[future]))
def generate_report(self, batch_result: BatchResult, output_path: str = None) -> str: """Generate conversion report."""
report = { 'summary': { 'total_files': batch_result.total_files, 'successful': batch_result.successful, 'failed': batch_result.failed, 'skipped': batch_result.skipped, 'success_rate': round(batch_result.successful / batch_result.total_files * 100, 1) if batch_result.total_files > 0 else 0, 'total_duration_seconds': round(batch_result.total_duration, 2), 'start_time': batch_result.start_time.isoforma
Source provenance
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recent repository activity
Audit
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Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
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Scenario-led draft for batch-cad-converter, ready for a manual X post.
batch-cad-converter: Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error han... 305 stars https://www.openagentskill.com/skills/datadrivenconstruction-batch-cad-converter?ref=x
Listing + install path for batch-cad-converter: https://www.openagentskill.com/skills/datadrivenconstruction-batch-cad-converter?ref=x Install: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --...
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Install targets
Codex install prompt
Install the "batch-cad-converter" agent skill from https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction/tree/main/1_DDC_Toolkit/CAD-Converters/batch-cad-converter. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"datadrivenconstruction-batch-cad-converter","task":"Install batch-cad-converter","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converter
Maintenance
fresh
16d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
305
72/100 Quality · 68/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · The SKILL.md excerpt is truncated, but the available content is sufficient to understand the skill's purpose and workflow.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
305 GitHub stars
Repo activity
305 stars, 80 forks
Maintenance
16d since push
License
MIT
Install
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converter
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converterDo not use when
Agent safety v2
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
high
Skill metadata references terminal, CLI, shell, subprocess, or command execution workflows.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20batch-cad-converter%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20batch-cad-converter%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/datadrivenconstruction-batch-cad-converter/install
Agent should check
Copy prompt
Task: Use batch-cad-converter in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20batch-cad-converter%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/datadrivenconstruction-batch-cad-converter/install
Install command: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converter
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/datadrivenconstruction-batch-cad-converter/install
LLM text format
/api/skills/datadrivenconstruction-batch-cad-converter/install?format=text
Find alternatives
/api/skills/search?q=batch-cad-converter&limit=3
Agent prompt
Use batch-cad-converter for this task. Review https://www.openagentskill.com/api/skills/datadrivenconstruction-batch-cad-converter/install, then install with: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converterRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/datadrivenconstruction-batch-cad-converter
LLM text
/api/registry/manifest/datadrivenconstruction-batch-cad-converter?format=text
Install alias
/api/registry/install/datadrivenconstruction-batch-cad-converter
Recommend
/api/registry/recommend?task=Use%20batch-cad-converter%20in%20an%20agent%20workflow&limit=3
Agent fit
Browser automation
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Browser automation
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO305 GitHub stars
Stars/forks activity
INFO305 stars, 80 forks; issue activity unavailable in current metadata
Recent maintenance
PASS16d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Automate repeated work
I need my agent to automate a repeated workflow across tools and files.
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Workflow fit
Turn skills into distribution
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Run multimodal agents that operate desktop interfaces
Connect agents to hundreds of workflow automations
利用AI大模型,一键生成高清短视频 Generate short videos with one click using AI LLM.
Alternative firmware for ESP8266 and ESP32 based devices with easy configuration using webUI, OTA updates, automation using timers or rules, expandability and entirely local control over MQTT, HTTP, Serial or KNX. Full documentation at
--- name: "batch-cad-converter" description: "Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error handling, and consolidated reporting." homepage: "https://datadrivenconstruction.io" metadata: {"openclaw":{"emoji":"🔄","os":["win32"],"homepage":"https://datadrivenconstruction.io","requires":{"bins":["python3"],"anyBins":["RvtExporter","DwgExporter","DgnExporter","RVT2IFCconverter"]}}} ---
# Batch CAD/BIM Converter
## Business Case
### Problem Statement Large projects and archives contain hundreds or thousands of CAD/BIM files: - Manual conversion is tedious and error-prone - Different formats require different converters - Progress tracking is needed for long operations - Error handling is critical for large batches
### Solution Unified batch converter handling all supported formats with progress tracking, error recovery, and consolidated reporting.
### Business Value - **Multi-format** - Revit, IFC, DWG, DGN in one workflow - **Error recovery** - Continue on failures - **Progress tracking** - Monitor large batches - **Reporting** - Consolidated conversion results
## Python Implementation
```python import subprocess from pathlib import Path from typing import List, Optional, Dict, Any, Callable from dataclasses import dataclass, field from datetime import datetime import time import json from enum import Enum from concurrent.futures import ThreadPoolExecutor, as_completed
class CADFormat(Enum): """Supported CAD/BIM formats.""" REVIT = (".rvt", ".rfa") IFC = (".ifc",) DWG = (".dwg",) DGN = (".dgn",)
class ConversionStatus(Enum): """Status of conversion operation.""" PENDING = "pending" CONVERTING = "converting" SUCCESS = "success" FAILED = "failed" SKIPPED = "skipped"
@dataclass class ConversionResult: """Result of single file conversion.""" input_file: str output_file: Optional[str] format: str status: ConversionStatus start_time: datetime end_time: Optional[datetime] duration_seconds: float error_message: Optional[str] = None file_size_kb: float = 0
@dataclass class BatchResult: """Result of batch conversion.""" total_files: int successful: int failed: int skipped: int total_duration: float results: List[ConversionResult] start_time: datetime end_time: datetime
class BatchCADConverter: """Batch convert multiple CAD/BIM files."""
# Default converter paths DEFAULT_CONVERTERS = { 'revit': 'RvtExporter.exe', 'ifc': 'IfcExporter.exe', 'dwg': 'DwgExporter.exe', 'dgn': 'DgnExporter.exe' }
def __init__(self, converter_dir: str = ".", converters: Dict[str, str] = None): self.converter_dir = Path(converter_dir) self.converters = converters or self.DEFAULT_CONVERTERS self.results: List[ConversionResult] = [] self.progress_callback: Optional[Callable] = None
def set_progress_callback(self, callback: Callable[[int, int, str], None]): """Set callback for progress updates.""" self.progress_callback = callback
def _get_format(self, file_path: Path) -> Optional[str]: """Detect CAD format from extension.""" ext = file_path.suffix.lower()
for format_name, extensions in [ ('revit', ('.rvt', '.rfa')), ('ifc', ('.ifc',)), ('dwg', ('.dwg',)), ('dgn', ('.dgn',)) ]: if ext in extensions: return format_name
return None
def _get_converter(self, format_name: str) -> Optional[Path]: """Get converter path for format.""" if format_name not in self.converters: return None
converter = self.converter_dir / self.converters[format_name] if converter.exists(): return converter
# Try in system PATH return Path(self.converters[format_name])
def convert_file(self, input_file: str, output_dir: Optional[str] = None, options: List[str] = None) -> ConversionResult: """Convert single file."""
input_path = Path(input_file) start_time = datetime.now()
# Detect format format_name = self._get_format(input_path) if not format_name: return ConversionResult( input_file=input_file, output_file=None, format='unknown', status=ConversionStatus.SKIPPED, start_time=start_time, end_time=datetime.now(), duration_seconds=0, error_message="Unsupported format" )
# Get converter converter = self._get_converter(format_name) if not converter: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=datetime.now(), duration_seconds=0, error_message=f"Converter not found for {format_name}" )
# Build command cmd = [str(converter), str(input_path)] if options: cmd.extend(options)
# Execute try: result = subprocess.run(cmd, capture_output=True, text=True, timeout=3600) end_time = datetime.now() duration = (end_time - start_time).total_seconds()
# Determine output file output_file = input_path.with_suffix('.xlsx') if output_dir: output_file = Path(output_dir) / output_file.name
if result.returncode == 0 and output_file.exists(): return ConversionResult( input_file=input_file, output_file=str(output_file), format=format_name, status=ConversionStatus.SUCCESS, start_time=start_time, end_time=end_time, duration_seconds=duration, file_size_kb=output_file.stat().st_size / 1024 ) else: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=end_time, duration_seconds=duration, error_message=result.stderr or "Conversion failed" )
except subprocess.TimeoutExpired: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=datetime.now(), duration_seconds=3600, error_message="Timeout exceeded (1 hour)" )
except Exception as e: return ConversionResult( input_file=input_file, output_file=None, format=format_name, status=ConversionStatus.FAILED, start_time=start_time, end_time=datetime.now(), duration_seconds=0, error_message=str(e) )
def batch_convert(self, input_folder: str, output_folder: Optional[str] = None, include_subfolders: bool = True, formats: List[str] = None, options: Dict[str, List[str]] = None, parallel: bool = False, max_workers: int = 4) -> BatchResult: """Convert all files in folder."""
start_time = datetime.now() input_path = Path(input_folder)
# Find all supported files files = [] pattern = "**/*" if include_subfolders else "*"
for ext in ['.rvt', '.rfa', '.ifc', '.dwg', '.dgn']: files.extend(input_path.glob(f"{pattern}{ext}"))
# Filter by format if specified if formats: files = [f for f in files if self._get_format(f) in formats]
total_files = len(files) self.results = []
# Create output directory if output_folder: Path(output_folder).mkdir(parents=True, exist_ok=True)
# Process files if parallel and total_files > 1: self._convert_parallel(files, output_folder, options, max_workers) else: self._convert_sequential(files, output_folder, options)
end_time = datetime.now()
# Calculate statistics successful = sum(1 for r in self.results if r.status == ConversionStatus.SUCCESS) failed = sum(1 for r in self.results if r.status == ConversionStatus.FAILED) skipped = sum(1 for r in self.results if r.status == ConversionStatus.SKIPPED)
return BatchResult( total_files=total_files, successful=successful, failed=failed, skipped=skipped, total_duration=(end_time - start_time).total_seconds(), results=self.results, start_time=start_time, end_time=end_time )
def _convert_sequential(self, files: List[Path], output_folder: Optional[str], options: Dict[str, List[str]]): """Convert files sequentially."""
total = len(files) for i, file_path in enumerate(files, 1): if self.progress_callback: self.progress_callback(i, total, str(file_path))
format_name = self._get_format(file_path) format_options = options.get(format_name, []) if options else []
result = self.convert_file(str(file_path), output_folder, format_options) self.results.append(result)
status_symbol = "✓" if result.status == ConversionStatus.SUCCESS else "✗" print(f"[{i}/{total}] {status_symbol} {file_path.name}")
def _convert_parallel(self, files: List[Path], output_folder: Optional[str], options: Dict[str, List[str]], max_workers: int): """Convert files in parallel."""
total = len(files)
with ThreadPoolExecutor(max_workers=max_workers) as executor: futures = {}
for file_path in files: format_name = self._get_format(file_path) format_options = options.get(format_name, []) if options else [] future = executor.submit(self.convert_file, str(file_path), output_folder, format_options) futures[future] = file_path
completed = 0 for future in as_completed(futures): completed += 1 result = future.result() self.results.append(result)
if self.progress_callback: self.progress_callback(completed, total, str(futures[future]))
def generate_report(self, batch_result: BatchResult, output_path: str = None) -> str: """Generate conversion report."""
report = { 'summary': { 'total_files': batch_result.total_files, 'successful': batch_result.successful, 'failed': batch_result.failed, 'skipped': batch_result.skipped, 'success_rate': round(batch_result.successful / batch_result.total_files * 100, 1) if batch_result.total_files > 0 else 0, 'total_duration_seconds': round(batch_result.total_duration, 2), 'start_time': batch_result.start_time.isoforma
Source provenance
Decision snapshot
recent repository activity
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for batch-cad-converter, ready for a manual X post.
batch-cad-converter: Batch convert multiple CAD/BIM files (Revit, IFC, DWG, DGN) with progress tracking, error han... 305 stars https://www.openagentskill.com/skills/datadrivenconstruction-batch-cad-converter?ref=x
Listing + install path for batch-cad-converter: https://www.openagentskill.com/skills/datadrivenconstruction-batch-cad-converter?ref=x Install: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --...
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[](https://www.openagentskill.com/skills/datadrivenconstruction-batch-cad-converter?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
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UI-TARS Desktop
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shell or command execution, filesystem or document access
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shell or command execution, filesystem or document access
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