schedule-delay-analyzer について
プロジェクトチーム向けのスケジュール遅延分析スキルです。作業、種類、原因、日付を関連付けて遅延を記録します。READMEには使用例がありますが、その他の分析結果は記載されていません。
主な機能
- 01遅延の詳細を記録
- 02遅延の種類を分類
- 03遅延原因を記録
- 04作業に遅延を関連付け
活用シーン
- 01予定作業に遅延を記録
- 02種類と原因による遅延の分類
インストール
コマンドをコピーしてターミナルで実行します。
$
npx skills add https:/ / github.com/ datadrivenconstruction/ ddc_skills_for_ai_agents_in_construction --skill schedule-delay-analyzerインストール後、Claude Code で/schedule-delay-analyzerを入力して読み込まれたか確認します。
同梱ファイルclaw.jsoninstructions.md
README(原文)English
プロジェクトの README よりこの README の日本語訳はまだありません。以下は英語の原文です。日本語の紹介はページ上部をご覧ください。
Schedule Delay Analyzer
Technical Implementation
import pandas as pd
from datetime import date, timedelta
from typing import Dict, Any, List, Optional
from dataclasses import dataclass, field
from enum import Enum
class DelayType(Enum):
EXCUSABLE_COMPENSABLE = "excusable_compensable"
EXCUSABLE_NON_COMPENSABLE = "excusable_non_compensable"
NON_EXCUSABLE = "non_excusable"
CONCURRENT = "concurrent"
class DelayCause(Enum):
OWNER_CHANGE = "owner_change"
DESIGN_ERROR = "design_error"
WEATHER = "weather"
DIFFERING_CONDITIONS = "differing_conditions"
CONTRACTOR_ISSUE = "contractor_issue"
MATERIAL_DELAY = "material_delay"
LABOR_SHORTAGE = "labor_shortage"
PERMIT_DELAY = "permit_delay"
OTHER = "other"
@dataclass
class DelayEvent:
delay_id: str
activity_id: str
activity_name: str
delay_type: DelayType
cause: DelayCause
start_date: date
end_date: date
delay_days: int
on_critical_path: bool
description: str
documentation: List[str] = field(default_factory=list)
cost_impact: float = 0.0
@dataclass
class ScheduleBaseline:
baseline_date: date
planned_completion: date
activities: Dict[str, Dict[str, date]] # activity_id: {start, end}
class ScheduleDelayAnalyzer:
def __init__(self, project_name: str, contract_completion: date):
self.project_name = project_name
self.contract_completion = contract_completion
self.baselines: List[ScheduleBaseline] = []
self.delays: Dict[str, DelayEvent] = {}
self._counter = 0
def add_baseline(self, baseline_date: date, planned_completion: date,
activities: Dict[str, Dict[str, date]]):
baseline = ScheduleBaseline(baseline_date, planned_completion, activities)
self.baselines.append(baseline)
def record_delay(self, activity_id: str, activity_name: str,
delay_type: DelayType, cause: DelayCause,
start_date: date, end_date: date,
on_critical_path: bool, description: str,
cost_impact: float = 0) -> DelayEvent:
self._counter += 1
delay_id = f"DLY-{self._counter:04d}"
delay = DelayEvent(
delay_id=delay_id,
activity_id=activity_id,
activity_name=activity_name,
delay_type=delay_type,
cause=cause,
start_date=start_date,
end_date=end_date,
delay_days=(end_date - start_date).days,
on_critical_path=on_critical_path,
description=description,
cost_impact=cost_impact
)
self.delays[delay_id] = delay
return delay
def calculate_project_delay(self) -> int:
"""Calculate total critical path delay."""
critical_delays = [d for d in self.delays.values() if d.on_critical_path]
return sum(d.delay_days for d in critical_delays)
def analyze_by_type(self) -> Dict[str, Dict[str, Any]]:
analysis = {}
for delay in self.delays.values():
dtype = delay.delay_type.value
if dtype not in analysis:
analysis[dtype] = {'count': 0, 'days': 0, 'cost': 0}
analysis[dtype]['count'] += 1
analysis[dtype]['days'] += delay.delay_days
analysis[dtype]['cost'] += delay.cost_impact
return analysis
def analyze_by_cause(self) -> Dict[str, int]:
by_cause = {}
for delay in self.delays.values():
cause = delay.cause.value
by_cause[cause] = by_cause.get(cause, 0) + delay.delay_days
return by_cause
def calculate_time_extension_claim(self) -> Dict[str, Any]:
"""Calculate basis for time extension claim."""
excusable = [d for d in self.delays.values()
if d.delay_type in [DelayType.EXCUSABLE_COMPENSABLE,
DelayType.EXCUSABLE_NON_COMPENSABLE]
and d.on_critical_path]
compensable = [d for d in excusable
if d.delay_type == DelayType.EXCUSABLE_COMPENSABLE]
return {
'excusable_delays': len(excusable),
'excusable_days': sum(d.delay_days for d in excusable),
'compensable_delays': len(compensable),
'compensable_days': sum(d.delay_days for d in compensable),
'total_cost_impact': sum(d.cost_impact for d in compensable),
'recommended_extension': sum(d.delay_days for d in excusable)
}
def get_summary(self) -> Dict[str, Any]:
critical_delay = self.calculate_project_delay()
projected_completion = self.contract_completion + timedelta(days=critical_delay)
return {
'project': self.project_name,
'contract_completion': self.contract_completion,
'projected_completion': projected_completion,
'total_delays': len(self.delays),
'critical_path_delays': sum(1 for d in self.delays.values() if d.on_critical_path),
'total_delay_days': critical_delay,
'by_type': self.analyze_by_type(),
'by_cause': self.analyze_by_cause()
}
def export_analysis(self, output_path: str):
data = [{
'ID': d.delay_id,
'Activity': d.activity_name,
'Type': d.delay_type.value,
'Cause': d.cause.value,
'Start': d.start_date,
'End': d.end_date,
'Days': d.delay_days,
'Critical': d.on_critical_path,
'Cost Impact': d.cost_impact,
'Description': d.description
} for d in self.delays.values()]
pd.DataFrame(data).to_excel(output_path, index=False)
Quick Start
analyzer = ScheduleDelayAnalyzer("Office Tower", date(2024, 12, 31))
delay = analyzer.record_delay(
activity_id="A-300",
activity_name="Foundation Work",
delay_type=DelayType.EXCUSABLE_COMPENSABLE,
cause=DelayCause.OWNER_CHANGE,
start_date=date(2024, 3, 1),
end_date=date(2024, 3, 15),
on_critical_path=True,
description="Owner requested additional scope",
cost_impact=50000
)
summary = analyzer.get_summary()
print(f"Project delayed by {summary['total_delay_days']} days")
claim = analyzer.calculate_time_extension_claim()
print(f"Recommended extension: {claim['recommended_extension']} days")
Resources
- DDC Book: Chapter 3.3 - Schedule Management
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