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xml-readerXML reader 搜索

Agent Skill

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

总安装

494

周安装

20

GitHub Stars

111

下载量

155
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:xml-reader(XML reader 搜索)
来源仓库:https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction
仓库路径:skills/xml-reader
安装命令:
npx skills add https://github.com/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction --skill xml-reader
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 xml-reader

简介

解析 P6 XER、IFC-XML 等建筑 XML 格式。

  • 转换为 DataFrame 便于后续分析。
  • 保留标签结构与属性信息完整。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。
  • 深层嵌套结构可能影响解析效率。
  • xml-reader 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

XML Reader for Construction Data

Overview

XML is used in construction for P6 schedules (XER), IFC-XML, COBie-XML, and buildingSMART Data Dictionary exports. This skill parses XML and converts to structured DataFrames.

Python Implementation

import xml.etree.ElementTree as ET
import pandas as pd
from typing import Dict, Any, List, Optional, Union
from dataclasses import dataclass
from pathlib import Path
import re

@dataclass
class XMLElement:
    """Parsed XML element."""
    tag: str
    attributes: Dict[str, str]
    text: Optional[str]
    children: List['XMLElement']

class ConstructionXMLReader:
    """Parse XML from construction systems."""

    def __init__(self):
        self.namespaces: Dict[str, str] = {}

    def parse_file(self, file_path: str) -> ET.Element:
        """Parse XML file and return root element."""
        tree = ET.parse(file_path)
        root = tree.getroot()

        # Extract namespaces
        self._extract_namespaces(root)

        return root

    def parse_string(self, xml_string: str) -> ET.Element:
        """Parse XML from string."""
        root = ET.fromstring(xml_string)
        self._extract_namespaces(root)
        return root

    def _extract_namespaces(self, root: ET.Element):
        """Extract namespace mappings."""
        # Find namespace declarations
        for attr, value in root.attrib.items():
            if attr.startswith('{'):
                ns = attr[1:attr.index('}')]
                self.namespaces[root.tag.split('}')[0][1:]] = ns

    def find_elements(self, root: ET.Element,
                      tag: str,
                      namespace: str = None) -> List[ET.Element]:
        """Find all elements with given tag."""
        if namespace:
            tag = f"{{{namespace}}}{tag}"
        return root.findall(f".//{tag}")

    def element_to_dict(self, element: ET.Element,
                        include_children: bool = True) -> Dict[str, Any]:
        """Convert element to dictionary."""
        result = {
            '_tag': element.tag.split('}')[-1] if '}' in element.tag else element.tag,
            '_text': element.text.strip() if element.text else None,
            **element.attrib
        }

        if include_children:
            for child in element:
                child_tag = child.tag.split('}')[-1] if '}' in child.tag else child.tag

                if child_tag in result:
                    # Multiple children with same tag - make list
                    if not isinstance(result[child_tag], list):
                        result[child_tag] = [result[child_tag]]
                    result[child_tag].append(self.element_to_dict(child))
                else:
                    result[child_tag] = self.element_to_dict(child)

        return result

    def elements_to_dataframe(self, elements: List[ET.Element]) -> pd.DataFrame:
        """Convert list of elements to DataFrame."""
        records = []
        for elem in elements:
            record = {'_tag': elem.tag.split('}')[-1]}
            record.update(elem.attrib)

            # Get direct text content
            if elem.text and elem.text.strip():
                record['_text'] = elem.text.strip()

            # Get child values
            for child in elem:
                child_tag = child.tag.split('}')[-1]
                if child.text and child.text.strip():
                    record[child_tag] = child.text.strip()
                # Also get child attributes
                for attr, val in child.attrib.items():
                    record[f"{child_tag}_{attr}"] = val

            records.append(record)

        return pd.DataFrame(records)

    def flatten_xml(self, root: ET.Element,
                    target_tag: str = None) -> pd.DataFrame:
        """Flatten XML to DataFrame."""
        if target_tag:
            elements = self.find_elements(root, target_tag)
        else:
            elements = list(root)

        return self.elements_to_dataframe(elements)

class P6XMLReader(ConstructionXMLReader):
    """Reader for Primavera P6 XML exports."""

    def parse_activities(self, root: ET.Element) -> pd.DataFrame:
        """Parse activities from P6 XML."""
        activities = self.find_elements(root, 'Activity')
        return self.elements_to_dataframe(activities)

    def parse_resources(self, root: ET.Element) -> pd.DataFrame:
        """Parse resources from P6 XML."""
        resources = self.find_elements(root, 'Resource')
        return self.elements_to_dataframe(resources)

    def parse_wbs(self, root: ET.Element) -> pd.DataFrame:
        """Parse WBS from P6 XML."""
        wbs = self.find_elements(root, 'WBS')
        return self.elements_to_dataframe(wbs)

    def parse_full_schedule(self, file_path: str) -> Dict[str, pd.DataFrame]:
        """Parse complete P6 schedule."""
        root = self.parse_file(file_path)
        return {
            'activities': self.parse_activities(root),
            'resources': self.parse_resources(root),
            'wbs': self.parse_wbs(root)
        }

class IFCXMLReader(ConstructionXMLReader):
    """Reader for IFC-XML files."""

    def parse_entities(self, root: ET.Element) -> pd.DataFrame:
        """Parse IFC entities."""
        # Find all Ifc* elements
        all_entities = []
        for elem in root.iter():
            if elem.tag.startswith('Ifc'):
                all_entities.append(elem)
        return self.elements_to_dataframe(all_entities)

    def get_entity_types(self, root: ET.Element) -> Dict[str, int]:
        """Count entity types."""
        counts = {}
        for elem in root.iter():
            tag = elem.tag
            if tag.startswith('Ifc'):
                counts[tag] = counts.get(tag, 0) + 1
        return counts

class COBieXMLReader(ConstructionXMLReader):
    """Reader for COBie XML files."""

    COBIE_SHEETS = ['Facility', 'Floor', 'Space', 'Zone', 'Type',
                    'Component', 'System', 'Assembly', 'Connection',
                    'Spare', 'Resource', 'Job', 'Document', 'Attribute']

    def parse_cobie(self, file_path: str) -> Dict[str, pd.DataFrame]:
        """Parse all COBie sheets."""
        root = self.parse_file(file_path)
        result = {}

        for sheet in self.COBIE_SHEETS:
            elements = self.find_elements(root, sheet)
            if elements:
                result[sheet] = self.elements_to_dataframe(elements)

        return result

class BSDDXMLReader(ConstructionXMLReader):
    """Reader for buildingSMART Data Dictionary exports."""

    def parse_classifications(self, root: ET.Element) -> pd.DataFrame:
        """Parse classification items."""
        items = self.find_elements(root, 'Classification')
        return self.elements_to_dataframe(items)

    def parse_properties(self, root: ET.Element) -> pd.DataFrame:
        """Parse property definitions."""
        props = self.find_elements(root, 'Property')
        return self.elements_to_dataframe(props)

Quick Start

reader = ConstructionXMLReader()

# Parse XML file
root = reader.parse_file("schedule.xml")

# Find specific elements
activities = reader.find_elements(root, "Activity")
print(f"Found {len(activities)} activities")

# Convert to DataFrame
df = reader.elements_to_dataframe(activities)

Common Use Cases

1. P6 Schedule Import

p6_reader = P6XMLReader()
schedule = p6_reader.parse_full_schedule("p6_export.xml")

activities = schedule['activities']
print(f"Activities: {len(activities)}")

2. COBie Data

cobie_reader = COBieXMLReader()
cobie_data = cobie_reader.parse_cobie("facility_cobie.xml")

components = cobie_data.get('Component', pd.DataFrame())

3. IFC-XML Analysis

ifc_reader = IFCXMLReader()
root = ifc_reader.parse_file("model.ifcxml")

# Count entity types
types = ifc_reader.get_entity_types(root)
for entity_type, count in sorted(types.items(), key=lambda x: -x[1])[:10]:
    print(f"{entity_type}: {count}")

Resources

  • DDC Book: Chapter 2.1 - Semi-structured Data
  • IFC-XML: buildingSMART specification

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.99%
按下载量换算54

Claude

31.3%
按下载量换算49

Cursor

15.98%
按下载量换算25

Gemini CLI

8.7%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

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安装前确认

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来源信息

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