bim-clash-detection

审查 · 64
已收录

Detect and analyze geometric clashes in BIM models. Identify MEP, structural, and architectural conflicts before construction.

Verified installs0
Stars282
版本1.0.0
质量71/100 ·
信任64/100 · 仅限沙盒
审计80/100 · 需审查

供给资产档案

数据、BI 与分析

CSV, SQL, notebooks, dashboards, data pipelines, BI, ETL, and spreadsheet analysis.

浏览赛道

场景

数据分析

I need my agent to analyze CSV data, produce insights, and explain trends.

适配 Agent

Claude Code + CLI + Codex

适用于 Codex、Claude Code、Cursor、CLI 或自定义 Agent。

安装

就绪

npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill bim-clash-detection

维护状态

新鲜

距上次推送 1 天

风险

需审查

The provided SKILL.md excerpt is truncated, but the full file is expected to be complete in the repository.

GitHub 质量

282

71/100 质量 · 72/100 信任

覆盖标签

数据数据分析自动化agent-skill

审查说明

The provided SKILL.md excerpt is truncated, but the full file is expected to be complete in the repository. · SKILL.md lacks explicit setup instructions and a clear step-by-step workflow for using the provided classes, relying on the agent to implement the detection logic.

Agent 采用评分卡

一眼查看信任、审计与安装准备度

这些分数综合公开仓库元数据、OpenAgentSkill 审查信号、维护新鲜度与安装准备度。它用于候选筛选,不替代人工审查。

质量

71

可靠的选择,值得加入生产工作流候选列表。

信任

仅限沙盒
64

有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。

审计

需审查
80

对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。

OpenAgentSkill 信任评分 v5

安装前需人工审查

仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。

CodexClaude CodeCursorOpenAgentSkill CLI

Stars

282 个 GitHub Stars

仓库活跃度

282 个 Star,74 个 Fork

维护状态

距上次推送 1 天

许可证

MIT

安装

npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill bim-clash-detection

安装安全性

标准软件包或运行时安装路径

权限范围

公开元数据中未发现高风险权限范围

Agent 结果

暂未有 Agent 结果数据

文档

Usable metadata, review docs

风险摘要

生产前审查

  • The provided SKILL.md excerpt is truncated, but the full file is expected to be complete in the repository.
  • Quality score needs review

安装准备度

安装路径可用

  • 安装路径可用
  • 仓库证据可用
  • 已声明许可证
  • 暂无 Agent 验证结果证据

Agent 可读元数据

这个 Skill 的机器可读决策数据。

使用此区块或内嵌 JSON 判断 Agent 是否应安装该 Skill、选择替代方案,或先请求人工审查。

打开 JSON

适用任务

  • Browser automation 工作流
  • Claude Code 团队
  • builders willing to evaluate younger projects
  • Navigate pages

适用 Agent

CodexClaude CodeCursorOpenAgentSkill CLICLI

安装决策

命令
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill bim-clash-detection
策略
审查
人工审查

信任与风险

信任
64/100
审计
80/100
风险级别
需审查

结果闭环

端点
/api/agent/outcome
事件 ID
resolve
结果
5

安装命令

npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill bim-clash-detection

不适用场景

  • 需要厂商支持 SLA 的团队
  • production agents without a repository review
  • The provided SKILL.md excerpt is truncated, but the full file is expected to be complete in the repository.
  • SKILL.md lacks explicit setup instructions and a clear step-by-step workflow for using the provided classes, relying on the agent to implement the detection logic.
  • No limitations or edge-case considerations are documented (e.g., bounding box approximation accuracy, handling of incomplete models).

Agent 安全 v2

68/100 · 安装前审查

已审查并附权限说明审查

可用候选,但 Agent 在安装前应展示权限与审计说明。

在真实工作区安装前需要人工批准。

通过 API 解析

网络访问

Skill 可能访问远程页面、API、仓库或外部服务。

  • The provided SKILL.md excerpt is truncated, but the full file is expected to be complete in the repository.

安装目标

在你的 Agent 工作流中安装此 Skill

通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。

skill install

OpenAgentSkill CLI

Resolve policy, run the source installer safely, and report a verified install receipt.

$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install datadrivenconstruction-bim-clash-detection

Agent 解析计划

让 Agent 在安装前验证匹配度。

Resolve API 返回首选 Skill、替代方案、安全策略、审计说明、安装目标和可直接执行的提示词,无需抓取此页面。

打开文本计划

Agent 应检查

  • 从 Resolve API 检查任务匹配与替代方案。
  • 检查审计评分、信任评分和安全策略警告。
  • 检查 Codex、Claude Code、Cursor 或 CLI 的安装目标兼容性。

复制提示词

Task: Use bim-clash-detection in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20bim-clash-detection%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/datadrivenconstruction-bim-clash-detection/install
Install command: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill bim-clash-detection
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.

Agent 交接

把安装路径交给 Agent,而不是再给一个目录页。

通过公开安装端点获取命令、安全清单、目标提示词和该 Skill 的规范链接。

打开安装 API

Agent 提示词

Use bim-clash-detection for this task. Review https://www.openagentskill.com/api/skills/datadrivenconstruction-bim-clash-detection/install, then install with: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill bim-clash-detection

Registry 元数据

用于自动选择 Skill 的 Agent 可读档案。

本页通过 Registry API 提供相同的决策、信任、审计、场景和安装信号,让 Agent 无需抓取界面即可排序。

打开 Manifest

适配 Agent

70/100

Browser automation

平台

Claude Code

审计报告

需审查 · 80/100

对安装准备度、安全元数据、维护情况与采用风险的机器可读审查。

查看审计报告查看评估报告

Agent 决策面板

Fallback candidate for Browser automation

先用此 Skill 做原型验证,并保留备选方案。

70
就绪度
原型验证
阶段

栈中角色

备选候选

主要匹配

Browser automation

信任标签

先做原型验证

安装路径

命令已就绪

适用场景

  • Browser automation 工作流
  • Claude Code 团队
  • builders willing to evaluate younger projects

证据

  • 仓库近期活跃
  • 已提供安装命令或 GitHub 仓库
  • 71/100 质量档案
  • 1 个 OpenAgentSkill 交互事件

先审查

  • The provided SKILL.md excerpt is truncated, but the full file is expected to be complete in the repository.

实施路径

  1. 1在沙盒 Agent 中安装它,并端到端完成一次Browser automation任务。
  2. 2Compare output quality, latency, and failure behavior against at least one alternative.
  3. 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.

信任档案

仅限沙盒

有用但信任信号不足或混杂的候选项。在结果闭环证明任务匹配前,请保持在隔离工作区内使用。

64
OpenAgentSkill 信任评分

GitHub 采用度

信息

282 个 GitHub Stars

Star/Fork 活跃度

信息

282 个 Star,74 个 Fork; 当前元数据中没有议题活跃度信息

近期维护

通过

距上次推送 1 天

许可证清晰度

通过

MIT

积极信号

  • AI 审查已通过
  • 安装路径可用
  • 仓库证据可用
  • 近期维护的仓库
  • 安装命令未发现明显高风险模式
  • 结果闭环已就绪,但需要首次真实 Agent 运行

安装前审查

  • The provided SKILL.md excerpt is truncated, but the full file is expected to be complete in the repository.
  • Quality score needs review
  • 暂未有真实 Agent 结果报告
  • 无人值守安装前需要人工审查

建议操作

仅在沙盒中运行,并在用于真实工作前比较接近的替代方案。

质量档案

适用于 Agent 工作流的候选

可靠的选择,值得加入生产工作流候选列表。

71
GitHub Stars
282
新鲜度
1 天前
安装就绪
许可证
MIT
安装前审查: The provided SKILL.md excerpt is truncated, but the full file is expected to be complete in the repository.

工作流匹配

在这些场景使用此 Skill

工作流匹配

加入完整工作流

替代方案短名单

安装前对比

可能适合该任务的相近 Skill。

对比全部

概览

--- name: "bim-clash-detection" description: "Detect and analyze geometric clashes in BIM models. Identify MEP, structural, and architectural conflicts before construction." homepage: "https://datadrivenconstruction.io" metadata: {"openclaw": {"emoji": "🔍", "os": ["darwin", "linux", "win32"], "homepage": "https://datadrivenconstruction.io", "requires": {"bins": ["python3"]}}} --- # BIM Clash Detection

## Business Case

### Problem Statement Coordination issues cause significant rework: - MEP vs structural conflicts discovered on site - Late design changes increase costs - Manual clash review is time-consuming - No standardized clash categorization

### Solution Automated clash detection and analysis system that identifies conflicts between building systems and provides prioritized resolution recommendations.

### Business Value - **Cost savings** - Detect issues before construction - **Time reduction** - Automated clash identification - **Better coordination** - Systematic conflict resolution - **Quality improvement** - Fewer field issues

## Technical Implementation

```python import pandas as pd from datetime import datetime from typing import Dict, Any, List, Optional, Tuple from dataclasses import dataclass, field from enum import Enum import math

class ClashType(Enum): """Types of clashes.""" HARD = "hard" # Physical intersection SOFT = "soft" # Clearance violation WORKFLOW = "workflow" # Sequencing conflict DUPLICATE = "duplicate" # Duplicated elements

class ClashStatus(Enum): """Clash resolution status.""" NEW = "new" ACTIVE = "active" RESOLVED = "resolved" APPROVED = "approved" IGNORED = "ignored"

class ClashSeverity(Enum): """Clash severity level.""" CRITICAL = "critical" MAJOR = "major" MINOR = "minor" INFO = "info"

class Discipline(Enum): """BIM disciplines.""" ARCHITECTURAL = "architectural" STRUCTURAL = "structural" MECHANICAL = "mechanical" ELECTRICAL = "electrical" PLUMBING = "plumbing" FIRE_PROTECTION = "fire_protection" CIVIL = "civil"

@dataclass class BoundingBox: """3D bounding box.""" min_x: float min_y: float min_z: float max_x: float max_y: float max_z: float

def intersects(self, other: 'BoundingBox') -> bool: """Check if boxes intersect.""" return (self.min_x <= other.max_x and self.max_x >= other.min_x and self.min_y <= other.max_y and self.max_y >= other.min_y and self.min_z <= other.max_z and self.max_z >= other.min_z)

def volume(self) -> float: """Calculate bounding box volume.""" return ((self.max_x - self.min_x) * (self.max_y - self.min_y) * (self.max_z - self.min_z))

def center(self) -> Tuple[float, float, float]: """Get center point.""" return ( (self.min_x + self.max_x) / 2, (self.min_y + self.max_y) / 2, (self.min_z + self.max_z) / 2 )

@dataclass class BIMElement: """BIM element representation.""" element_id: str name: str discipline: Discipline category: str # e.g., "Duct", "Beam", "Pipe" level: str bounding_box: BoundingBox properties: Dict[str, Any] = field(default_factory=dict)

def distance_to(self, other: 'BIMElement') -> float: """Calculate distance between element centers.""" c1 = self.bounding_box.center() c2 = other.bounding_box.center() return math.sqrt( (c2[0] - c1[0])**2 + (c2[1] - c1[1])**2 + (c2[2] - c1[2])**2 )

@dataclass class Clash: """Clash between two elements.""" clash_id: str element_a: BIMElement element_b: BIMElement clash_type: ClashType severity: ClashSeverity status: ClashStatus distance: float # Penetration depth (negative) or clearance gap location: Tuple[float, float, float] detected_at: datetime resolved_at: Optional[datetime] = None assigned_to: Optional[str] = None notes: str = ""

def to_dict(self) -> Dict[str, Any]: return { 'clash_id': self.clash_id, 'element_a_id': self.element_a.element_id, 'element_a_name': self.element_a.name, 'element_a_discipline': self.element_a.discipline.value, 'element_b_id': self.element_b.element_id, 'element_b_name': self.element_b.name, 'element_b_discipline': self.element_b.discipline.value, 'clash_type': self.clash_type.value, 'severity': self.severity.value, 'status': self.status.value, 'distance': round(self.distance, 3), 'location_x': self.location[0], 'location_y': self.location[1], 'location_z': self.location[2], 'level': self.element_a.level, 'detected_at': self.detected_at.isoformat(), 'assigned_to': self.assigned_to, 'notes': self.notes }

@dataclass class ClashTest: """Clash test configuration.""" name: str discipline_a: Discipline discipline_b: Discipline clash_type: ClashType tolerance: float = 0.0 # Clearance tolerance in meters enabled: bool = True

class BIMClashDetector: """Detect and manage BIM clashes."""

def __init__(self): self.elements: List[BIMElement] = [] self.clashes: List[Clash] = [] self.clash_tests: List[ClashTest] = [] self._clash_counter = 0

def load_elements(self, elements_df: pd.DataFrame) -> int: """Load BIM elements from DataFrame.""" loaded = 0 for _, row in elements_df.iterrows(): element = BIMElement( element_id=str(row.get('element_id', '')), name=str(row.get('name', '')), discipline=Discipline(row.get('discipline', 'architectural')), category=str(row.get('category', '')), level=str(row.get('level', '')), bounding_box=BoundingBox( min_x=float(row.get('min_x', 0)), min_y=float(row.get('min_y', 0)), min_z=float(row.get('min_z', 0)), max_x=float(row.get('max_x', 0)), max_y=float(row.get('max_y', 0)), max_z=float(row.get('max_z', 0)) ) ) self.elements.append(element) loaded += 1 return loaded

def add_clash_test(self, test: ClashTest): """Add clash test configuration.""" self.clash_tests.append(test)

def setup_standard_tests(self): """Setup standard MEP coordination tests.""" standard_tests = [ ClashTest("MEP vs Structure", Discipline.MECHANICAL, Discipline.STRUCTURAL, ClashType.HARD), ClashTest("Electrical vs Structure", Discipline.ELECTRICAL, Discipline.STRUCTURAL, ClashType.HARD), ClashTest("Plumbing vs Structure", Discipline.PLUMBING, Discipline.STRUCTURAL, ClashType.HARD), ClashTest("MEP vs MEP", Discipline.MECHANICAL, Discipline.ELECTRICAL, ClashType.HARD), ClashTest("Duct Clearance", Discipline.MECHANICAL, Discipline.MECHANICAL, ClashType.SOFT, tolerance=0.05), ClashTest("Fire Protection", Discipline.FIRE_PROTECTION, Discipline.STRUCTURAL, ClashType.HARD), ] for test in standard_tests: self.add_clash_test(test)

def run_clash_detection(self) -> List[Clash]: """Run all clash tests.""" new_clashes = []

for test in self.clash_tests: if not test.enabled: continue

# Filter elements by discipline elements_a = [e for e in self.elements if e.discipline == test.discipline_a] elements_b = [e for e in self.elements if e.discipline == test.discipline_b]

# Check all pairs for elem_a in elements_a: for elem_b in elements_b: if elem_a.element_id == elem_b.element_id: continue

clash = self._check_clash(elem_a, elem_b, test) if clash: new_clashes.append(clash)

self.clashes.extend(new_clashes) return new_clashes

def _check_clash(self, elem_a: BIMElement, elem_b: BIMElement, test: ClashTest) -> Optional[Clash]: """Check if two elements clash."""

# Expand bounding box by tolerance for soft clashes box_a = elem_a.bounding_box box_b = elem_b.bounding_box

if test.clash_type == ClashType.SOFT: # Add clearance tolerance expanded_a = BoundingBox( box_a.min_x - test.tolerance, box_a.min_y - test.tolerance, box_a.min_z - test.tolerance, box_a.max_x + test.tolerance, box_a.max_y + test.tolerance, box_a.max_z + test.tolerance ) intersects = expanded_a.intersects(box_b) else: intersects = box_a.intersects(box_b)

if not intersects: return None

# Calculate clash point and severity self._clash_counter += 1 clash_id = f"CLH-{self._clash_counter:05d}"

# Clash location (center of intersection) location = ( (max(box_a.min_x, box_b.min_x) + min(box_a.max_x, box_b.max_x)) / 2, (max(box_a.min_y, box_b.min_y) + min(box_a.max_y, box_b.max_y)) / 2, (max(box_a.min_z, box_b.min_z) + min(box_a.max_z, box_b.max_z)) / 2 )

# Calculate penetration depth distance = elem_a.distance_to(elem_b)

# Determine severity if test.clash_type == ClashType.HARD: severity = ClashSeverity.CRITICAL if distance < 0.1 else ClashSeverity.MAJOR else: severity = ClashSeverity.MINOR if distance > test.tolerance else ClashSeverity.MAJOR

return Clash( clash_id=clash_id, element_a=elem_a, element_b=elem_b, clash_type=test.clash_type, severity=severity, status=ClashStatus.NEW, distance=distance, location=location, detected_at=datetime.now() )

def get_summary(self) -> Dict[str, Any]: """Get clash detection summary.""" by_severity = {} by_discipline = {} by_status = {}

for clash in self.clashes: # By severity sev = clash.severity.value by_severity[sev] = by_severity.get(sev, 0) + 1

# By discipline pair pair = f"{clash.element_a.discipline.value} vs {clash.element_b.discipline.value}" by_discipline[pair] = by_discipline.get(pair, 0) + 1

# By status stat = clash.status.value by_status[stat] = by_status.get(stat, 0) + 1

return { 'total_clashes': len(self.clashes), 'by_severity': by_severity, 'by_discipline': by_discipline, 'by_status': by_status, 'elements_checked': len(self.elements), 'tests_run': len([t for t in self.clash_tests if t.enabled]) }

def export_to_dataframe(self) -> pd.DataFrame: """Export clashes to DataFrame.""" return pd.DataFrame([c.to_dict() for c in self.clashes])

def resolve_clash(self, clash_id: str, resolution_note: str): """Mark clash as resolved.""" for clash in self.clashes: if clash.clash_id == clash_id: clash.status = ClashStatus.RESOLVED clash.resolved_at = datetime.now() clash.notes = resolution_note break

def assign_clash(self, clash_id: str, assignee: str): """Assign clash to team member.""" for clash in self.clashes: if clash.clash_id ==

技术详情

版本
1.0.0
许可证
MIT
最近更新
2026年8月22日
发布时间
2026年8月22日

决策摘要

备选候选

70
就绪
原型验证
阶段

仓库近期活跃

审计

安装审查

安装与采用审查

80
需审查
安全性
83/100
维护状态
100/100
安装
92/100
打开完整审计查看评估报告

Agent 验证证据

Agent 验证证据

来自解析、审查、安装和一次小范围运行后的结果报告。

0
已验证
Needs first agent run自动安装: 先审查最近: 未知
成功率
近期失败
结果
0
输出质量
失败
0
不相关
0
安装次数
0
风险拦截
0
需要配置
0
生产环境
0

暂时没有 Agent 结果数据。首次 Agent 执行可以通过 /api/agent/outcome 报告成功、需要设置、风险拦截、失败或不相关。

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X

为 bim-clash-detection 准备的场景化草稿,可手动发布到 X。

策展说明
bim-clash-detection: Detect and analyze geometric clashes in BIM models. Identify MEP, structural, and architectur...

282 stars

https://www.openagentskill.com/skills/datadrivenconstruction-bim-clash-detection?ref=x
打开 X 草稿
可选:带安装命令的回复
Listing + install path for bim-clash-detection:
https://www.openagentskill.com/skills/datadrivenconstruction-bim-clash-detection?ref=x

Install: npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --...
打开回复草稿

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这条 Registry 收录 列表归属于 datadrivenconstruction,但尚未标记为官方。认领后可增加已验证所有者信号,使后续发布、安装和审计更新更值得信赖。

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作者

D

datadrivenconstruction

@datadrivenconstruction

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健康信号

GitHub Stars
282
质量评分
40/100
最近 GitHub 推送
2026年8月22日
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1
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仅限沙盒

64
  • GitHub 采用度282 个 GitHub Stars信息
  • Star/Fork 活跃度282 个 Star,74 个 Fork; 当前元数据中没有议题活跃度信息信息
  • 近期维护距上次推送 1 天通过
  • 许可证清晰度MIT通过
  • README/SKILL.md 完整度公开元数据需要更完整的 README/SKILL.md 上下文信息
  • 依赖与运行时风险公开元数据中未发现主要依赖风险提示通过