Create 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt integration.
日本語の概要は準備中です。原文の説明を表示しています。
Track construction submittals through the review process. Manage approvals, revisions, and compliance.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Submittals require careful tracking to avoid delays. This skill manages the entire submittal workflow from creation to approval.
import pandas as pd
from datetime import datetime, date, timedelta
from typing import Dict, Any, List, Optional
from dataclasses import dataclass, field
from enum import Enum
class SubmittalStatus(Enum):
DRAFT = "draft"
SUBMITTED = "submitted"
UNDER_REVIEW = "under_review"
APPROVED = "approved"
APPROVED_AS_NOTED = "approved_as_noted"
REVISE_RESUBMIT = "revise_resubmit"
REJECTED = "rejected"
class SubmittalType(Enum):
PRODUCT_DATA = "product_data"
SHOP_DRAWING = "shop_drawing"
SAMPLE = "sample"
MOCK_UP = "mock_up"
CERTIFICATE = "certificate"
TEST_REPORT = "test_report"
@dataclass
class ReviewComment:
reviewer: str
comment: str
comment_date: date
resolved: bool = False
@dataclass
class Submittal:
submittal_id: str
spec_section: str
title: str
submittal_type: SubmittalType
status: SubmittalStatus
contractor: str
revision: int
submitted_date: Optional[date]
required_date: date
approved_date: Optional[date] = None
comments: List[ReviewComment] = field(default_factory=list)
files: List[str] = field(default_factory=list)
class SubmittalTracker:
def __init__(self, project_name: str):
self.project_name = project_name
self.submittals: Dict[str, Submittal] = {}
self._counter = 0
def create_submittal(self, spec_section: str, title: str,
submittal_type: SubmittalType, contractor: str,
required_date: date) -> Submittal:
self._counter += 1
sub_id = f"SUB-{self._counter:04d}"
submittal = Submittal(
submittal_id=sub_id,
spec_section=spec_section,
title=title,
submittal_type=submittal_type,
status=SubmittalStatus.DRAFT,
contractor=contractor,
revision=0,
submitted_date=None,
required_date=required_date
)
self.submittals[sub_id] = submittal
return submittal
def submit(self, sub_id: str, files: List[str]):
if sub_id in self.submittals:
self.submittals[sub_id].status = SubmittalStatus.SUBMITTED
self.submittals[sub_id].submitted_date = date.today()
self.submittals[sub_id].files = files
def review(self, sub_id: str, status: SubmittalStatus, reviewer: str, comment: str = ""):
if sub_id in self.submittals:
sub = self.submittals[sub_id]
sub.status = status
if comment:
sub.comments.append(ReviewComment(reviewer, comment, date.today()))
if status in [SubmittalStatus.APPROVED, SubmittalStatus.APPROVED_AS_NOTED]:
sub.approved_date = date.today()
def resubmit(self, sub_id: str, files: List[str]):
if sub_id in self.submittals:
sub = self.submittals[sub_id]
sub.revision += 1
sub.status = SubmittalStatus.SUBMITTED
sub.submitted_date = date.today()
sub.files = files
def get_pending(self) -> List[Submittal]:
return [s for s in self.submittals.values()
if s.status in [SubmittalStatus.SUBMITTED, SubmittalStatus.UNDER_REVIEW]]
def get_overdue(self) -> List[Submittal]:
today = date.today()
return [s for s in self.submittals.values()
if s.status not in [SubmittalStatus.APPROVED, SubmittalStatus.APPROVED_AS_NOTED]
and s.required_date < today]
def export_log(self, output_path: str):
data = [{
'ID': s.submittal_id,
'Spec': s.spec_section,
'Title': s.title,
'Type': s.submittal_type.value,
'Status': s.status.value,
'Rev': s.revision,
'Submitted': s.submitted_date,
'Required': s.required_date,
'Approved': s.approved_date
} for s in self.submittals.values()]
pd.DataFrame(data).to_excel(output_path, index=False)
tracker = SubmittalTracker("Office Tower")
sub = tracker.create_submittal("09 29 00", "Gypsum Board",
SubmittalType.PRODUCT_DATA, "ABC Drywall",
date.today() + timedelta(days=14))
tracker.submit(sub.submittal_id, ["spec_sheet.pdf"])
tracker.review(sub.submittal_id, SubmittalStatus.APPROVED, "Architect")
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Create 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt integration.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze 5000+ IFC and Revit projects at scale for patterns, benchmarks, and insights. Big data analysis for construction.
日本語の概要は準備中です。原文の説明を表示しています。
Check construction AI systems against the EU AI Act (Regulation 2024/1689): classify risk of estimation, scheduling, CV and agent tools, document transparency, keep human oversight. Use when deploying or auditing AI in construction.
日本語の概要は準備中です。原文の説明を表示しています。
Orchestrate multiple AI agents for construction workflows: estimator, scheduler, document, QA and safety agents coordinated by a supervisor agent, with human checkpoints. Use when automating end-to-end project processes with agentic AI.
日本語の概要は準備中です。原文の説明を表示しています。
Create Apache Airflow DAGs for construction data pipelines. Orchestrate ETL, validation, and reporting workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Automate as-built documentation and digital handover for construction. Compile project records, generate O&M manuals, create asset databases, and ensure complete project closeout.
日本語の概要は準備中です。原文の説明を表示しています。