关于 schedule-delay-analyzer
面向项目团队的进度延误分析技能,可按活动记录延误类型、原因和日期;README 提供了使用示例,但未说明其他分析结果。
主要功能
- 01记录延误详情
- 02分类延误类型
- 03记录延误原因
- 04关联相关活动
适用场景
- 01将延误登记到计划活动
- 02按类型和原因分类延误
安装
复制下面的命令,在终端中运行。
$
npx skills add https:/ / github.com/ datadrivenconstruction/ ddc_skills_for_ai_agents_in_construction --skill schedule-delay-analyzer安装后在 Claude Code 中输入/schedule-delay-analyzer确认已加载。
附带文件claw.jsoninstructions.md
README 原文English
来自项目 READMEREADME 暂无中文译文,以下为英文原文;中文介绍见上方。
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
评论
支持 Markdown