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Agent Skill · 研究检索

batch-cad-converter(批量 CAD 转换器)

batch-cad-converter 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

batch-cad-converter 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 50,332。

总安装 618周安装 26GitHub Stars 113下载 216核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:batch-cad-converter(批量 CAD 转换器)
来源仓库:https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction
仓库路径:skills/batch-cad-converter
安装命令:
npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill batch-cad-converter
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill batch-cad-converter

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

batch-cad-converter 用于批量转换 CAD/BIM 文件,支持 Revit、IFC、DWG、DGN 等格式互转。适合大型项目归档或多格式交付场景,提供进度追踪与错误恢复机制。自动识别输入格式,并行处理文件并生成统一报告,减少人工干预。

安装命令:npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill batch-cad-converter。使用前请备份原始文件,避免因转换失败导致数据不可逆损坏。

来源仓库内路径:skills/batch-cad-converter

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agent…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

batch-cad-converter 怎么安装?

在终端执行 npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_const…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

batch-cad-converter 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

batch-cad-converter 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill batch-cad-converter 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

batch-cad-converter 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

batch-cad-converter 用的人多吗?

公开数据是累计安装 618 次,近一周安装 26 次,下载 216 次,GitHub 113 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

batch-cad-converter 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
batch-cad-converter

批量 CAD 转换器 · 本页

618113执行命令未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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}")

Quick Start

# Initialize batch converter
converter = BatchCADConverter(converter_dir="C:/DDC/")

# Set progress callback
converter.set_progress_callback(print_progress)

# Convert all files
result = converter.batch_convert(
    input_folder="C:/Projects",
    output_folder="C:/Converted",
    include_subfolders=True
)

print(f"Success: {result.successful}/{result.total_files}")

Common Use Cases

1. Convert Specific Formats Only

result = converter.batch_convert(
    input_folder="C:/Archive",
    formats=['revit', 'ifc'],  # Only Revit and IFC
    parallel=True,
    max_workers=4
)

2. With Format-Specific Options

options = {
    'revit': ['complete', 'bbox', 'rooms'],
    'ifc': ['bbox'],
    'dwg': []
}
result = converter.batch_convert(
    input_folder="C:/Projects",
    options=options
)

3. Generate Report

result = converter.batch_convert("C:/Projects")
report = converter.generate_report(result, "conversion_report.json")

Resources

平台分布

Codex

37.29%
按下载量换算81

Claude

30.78%
按下载量换算66

Cursor

19.27%
按下载量换算42

Gemini CLI

8.49%
按下载量换算18

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill batch-cad-converter 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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