batch-cad-converter

batch-cad-converter is a skill for Claude Code, Codex from datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction. It costs 36 tokens per session (2,886 once invoked), scanned A, original, MIT.

A batch converter for computer-aided design (CAD) and BIM files, which are digital drawings and building models. It supports Revit, IFC, DWG, and DGN files and records conversion progress and results.

In plain words
What is it for?
Use it to convert many Revit, IFC, DWG, or DGN files, monitor long conversion jobs, continue after errors, and review a combined report.
Why use it?
It removes the need to convert large collections of files one at a time and makes failures visible without stopping the whole batch.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to convert many Revit, IFC, DWG, or DGN files, monitor long conversion jobs, continue after errors, and review a combined report.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/batch-cad-converter
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill batch-cad-converter
Clone the repo
git clone --depth 1 https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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Your own site
<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/batch-cad-converter"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/batch-cad-converter/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/batch-cad-converter"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/batch-cad-converter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,886 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00036 $0.02886
Opus 5 $0.00018 $0.01443
Sonnet 5 $0.00007 $0.00577
Haiku 4.5 $0.00004 $0.00289

Measured 12d ago against content hash 675c582c1c7a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

batch-cad-converter scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

result = subprocess.run(cmd, capture_output=True, text=True, timeout=3600)
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

1_DDC_Toolkit/CAD-Converters/batch-cad-converter/SKILL.md · 429 lines

How it starts

The opening of the file, as written. The whole thing — 429 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

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.isoformat(),
                'end_time': batch_result.end_time.isoformat()
            },
            'results': [
                {
                    'input': r.input_file,
                    'output': r.output_file,
                    'format': r.format,
                    'status': r.status.value,
                    'duration': round(r.duration_seconds, 2),
                    'error': r.error_message
                }
                for r in batch_result.results
            ]
        }

        report_json = json.dumps(report, indent=2)

        if output_path:
            with open(output_path, 'w') as f:
                f.write(report_json)

        return report_json


# Progress callback example
def print_progress(current: int, total: int, file_name: str):
    """Print progress to console."""
    percent = current / total * 100
    print(f"Progress: {current}/{total} ({percent:.1f}%) - {file_name}")

Read the full file on GitHub · 429 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 429 lines · 36 tokens per session scan A 675c582c1c7a

Subscribe to this mod's changes

batch-cad-converter is a skill published in the GitHub repository datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction (310 stars, last pushed 20d ago), licensed MIT. It adds 36 tokens to every session and 2,886 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.