daily-progress-report
Generate automated daily progress reports from site data. Track work completed, labor hours, equipment usage, and weather conditions.
Install / Use
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill daily-progress-reportInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
Our assessment of daily-progress-report
daily-progress-report scores 89/100 on our quality scale, 1399th of 2,864 Automation skills we index (top 49%).
Its SKILL.md is 12 KB long, well organised into 16 sections with 5 code examples: a thorough specification that gives an agent plenty to work with.
It has 333 GitHub stars, a meaningful sign that others use it.
Maintenance, license and trust
- The repository was last updated 44 days ago, so daily-progress-report is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
daily-progress-report compared with similar skills
All 4 of these similar skills score higher than daily-progress-report; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| daily-progress-report (this skill)by datadrivenconstruction | 89 | 333 | 44d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 91.2k | 19d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 74.4k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 85.7k | today | MCP Server |
| crawl4aiby unclecode | 100 | 84.8k | today | MCP Server |
Frequently asked questions
- How do I install daily-progress-report?
- Run
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill daily-progress-report. The install tabs above show the steps for each supported agent. - Which AI agents does daily-progress-report work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is daily-progress-report safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is daily-progress-report still maintained?
- The repository was last updated 44 days ago, so daily-progress-report is actively maintained.
Skill content
View source on GitHubname: "daily-progress-report" description: "Generate automated daily progress reports from site data. Track work completed, labor hours, equipment usage, and weather conditions." homepage: "https://datadrivenconstruction.io" metadata: {"openclaw": {"emoji": "📊", "os": ["darwin", "linux", "win32"], "homepage": "https://datadrivenconstruction.io", "requires": {"bins": ["python3"]}}}
Daily Progress Report Generator
Business Case
Problem Statement
Site managers spend hours creating daily reports:
- Manual data collection
- Inconsistent formats
- Delayed submissions
- Missing information
Solution
Automated daily progress report generation from structured site data inputs.
Technical Implementation
import pandas as pd
from datetime import datetime, date
from typing import Dict, Any, List
from dataclasses import dataclass
from enum import Enum
class WeatherCondition(Enum):
CLEAR = "clear"
CLOUDY = "cloudy"
RAIN = "rain"
SNOW = "snow"
WIND = "wind"
EXTREME = "extreme"
class WorkStatus(Enum):
COMPLETED = "completed"
IN_PROGRESS = "in_progress"
DELAYED = "delayed"
NOT_STARTED = "not_started"
@dataclass
class WorkActivity:
activity_id: str
description: str
location: str
planned_qty: float
actual_qty: float
unit: str
status: WorkStatus
crew_size: int
hours_worked: float
notes: str = ""
@dataclass
class LaborEntry:
trade: str
company: str
workers: int
hours: float
overtime_hours: float = 0
@dataclass
class EquipmentEntry:
equipment_type: str
equipment_id: str
hours_used: float
status: str # active, idle, maintenance
operator: str = ""
@dataclass
class DailyReport:
report_date: date
project_name: str
project_number: str
weather: WeatherCondition
temperature_high: float
temperature_low: float
work_activities: List[WorkActivity]
labor: List[LaborEntry]
equipment: List[EquipmentEntry]
delays: List[str]
safety_incidents: int
visitors: List[str]
deliveries: List[str]
prepared_by: str
class DailyProgressReporter:
"""Generate daily progress reports."""
def __init__(self, project_name: str, project_number: str):
self.project_name = project_name
self.project_number = project_number
def create_report(self,
report_date: date,
weather: WeatherCondition,
temp_high: float,
temp_low: float,
prepared_by: str) -> DailyReport:
"""Create new daily report."""
return DailyReport(
report_date=report_date,
project_name=self.project_name,
project_number=self.project_number,
weather=weather,
temperature_high=temp_high,
temperature_low=temp_low,
work_activities=[],
labor=[],
equipment=[],
delays=[],
safety_incidents=0,
visitors=[],
deliveries=[],
prepared_by=prepared_by
)
def add_work_activity(self,
report: DailyReport,
activity_id: str,
description: str,
location: str,
planned_qty: float,
actual_qty: float,
unit: str,
crew_size: int,
hours_worked: float,
notes: str = ""):
"""Add work activity to report."""
# Determine status
if actual_qty >= planned_qty:
status = WorkStatus.COMPLETED
elif actual_qty > 0:
status = WorkStatus.IN_PROGRESS
elif actual_qty == 0 and planned_qty > 0:
status = WorkStatus.DELAYED
else:
status = WorkStatus.NOT_STARTED
activity = WorkActivity(
activity_id=activity_id,
description=description,
location=location,
planned_qty=planned_qty,
actual_qty=actual_qty,
unit=unit,
status=status,
crew_size=crew_size,
hours_worked=hours_worked,
notes=notes
)
report.work_activities.append(activity)
def add_labor(self,
report: DailyReport,
trade: str,
company: str,
workers: int,
hours: float,
overtime_hours: float = 0):
"""Add labor entry."""
report.labor.append(LaborEntry(
trade=trade,
company=company,
workers=workers,
hours=hours,
overtime_hours=overtime_hours
))
def add_equipment(self,
report: DailyReport,
equipment_type: str,
equipment_id: str,
hours_used: float,
status: str,
operator: str = ""):
"""Add equipment entry."""
report.equipment.append(EquipmentEntry(
equipment_type=equipment_type,
equipment_id=equipment_id,
hours_used=hours_used,
status=status,
operator=operator
))
def calculate_summary(self, report: DailyReport) -> Dict[str, Any]:
"""Calculate report summary metrics."""
total_workers = sum(l.workers for l in report.labor)
total_manhours = sum(l.workers * l.hours for l in report.labor)
total_overtime = sum(l.workers * l.overtime_hours for l in report.labor)
equipment_hours = sum(e.hours_used for e in report.equipment)
completed = sum(1 for a in report.work_activities if a.status == WorkStatus.COMPLETED)
in_progress = sum(1 for a in report.work_activities if a.status == WorkStatus.IN_PROGRESS)
delayed = sum(1 for a in report.work_activities if a.status == WorkStatus.DELAYED)
return {
'total_workers': total_workers,
'total_manhours': round(total_manhours, 1),
'total_overtime': round(total_overtime, 1),
'equipment_hours': round(equipment_hours, 1),
'activities_completed': completed,
'activities_in_progress': in_progress,
'activities_delayed': delayed,
'safety_incidents': report.safety_incidents,
'deliveries_count': len(report.deliveries)
}
def export_to_excel(self, report: DailyReport, output_path: str) -> str:
"""Export report to Excel."""
with pd.ExcelWriter(output_path, engine='openpyxl') as writer:
# Header
header_df = pd.DataFrame([{
'Project': report.project_name,
'Project #': report.project_number,
'Date': report.report_date,
'Weather': report.weather.value,
'High Temp': report.temperature_high,
'Low Temp': report.temperature_low,
'Prepared By': report.prepared_by
}])
header_df.to_excel(writer, sheet_name='Summary', index=False)
# Work Activities
if report.work_activities:
activities_df = pd.DataFrame([
{
'Activity ID': a.activity_id,
'Description': a.description,
'Location': a.location,
'Planned': a.planned_qty,
'Actual': a.actual_qty,
'Unit': a.unit,
'Status': a.status.value,
'Crew': a.crew_size,
'Hours': a.hours_worked,
'Notes': a.notes
}
for a in report.work_activities
])
activities_df.to_excel(writer, sheet_name='Work Activities', index=False)
# Labor
if report.labor:
labor_df = pd.DataFrame([
{
'Trade': l.trade,
'Company': l.company,
'Workers': l.workers,
'Hours': l.hours,
'Overtime': l.overtime_hours,
'Total Hours': l.workers * (l.hours + l.overtime_hours)
}
for l in report.labor
])
labor_df.to_excel(writer, sheet_name='Labor', index=False)
# Equipment
if report.equipment:
equip_df = pd.DataFrame([
{
'Type': e.equipment_type,
'ID': e.equipment_id,
'Hours': e.hours_used,
'Status': e.status,
'Operator': e.operator
}
for e in report.equipment
])
equip_df.to_excel(writer, sheet_name='Equipment', index=False)
return output_path
def generate_text_report(self, report: DailyReport) -> str:
"""Generate text version of report."""
summary = self.calculate_summary(report)
lines = [
f"DAILY PROGRESS REPORT",
f"=" * 50,
f"Project: {report.project_name}",
f"Project #: {report.project_number}",
f"Date: {report.report_date}",
f"Prepared by: {report.prepared_by}",
f"",
f"WEATHER CONDITIONS",
f"-" * 30,
f"Conditions: {report.weather.value}",
f"Temperature: {report.temperature_low}°C - {report.temperature_high}°C",
f"",
f"SUMMARY",
f"-" * 30,
f"Total Workers: {summary['total_workers']}",
f"Total Man-hours: {summary['total_manhours']}",
f"Equipment Hours: {summary['equipment_hours']}",
f"Activities Completed: {summary['activities_completed']}",
f"Activities In Progress: {summary['activities_in_progress']}",
f"Activities Delayed: {summary['activities_delayed']}",
f"Safety Incidents: {summary['safety_incidents']}",
]
if report.delays:
lines.extend([f"", f"DELAYS", f"-" * 30])
for delay in report.delays:
lines.append(f"• {delay}")
return "\n".join(lines)
Quick Start
from datetime import date
# Initialize reporter
reporter = DailyProgressReporter("Office Tower A", "PRJ-2024-001")
# Create report
report = reporter.create_report(
report_date=date.today(),
weather=WeatherCondition.CLEAR,
temp_high=28,
temp_low=18,
prepared_by="John Smith"
)
# Add activities
reporter.add_work_activity(
report,
activity_id="A-101",
description="Pour concrete slab Level 3",
location="Level 3, Zone A",
planned_qty=150,
actual_qty=150,
unit="m3",
crew_size=8,
hours_worked=10
)
# Add labor
reporter.add_labor(report, "Concrete", "ABC Concrete Co", 8, 10, 2)
# Export
reporter.export_to_excel(report, "daily_report.xlsx")
Common Use Cases
1. Generate Text Summary
text = reporter.generate_text_report(report)
print(text)
2. Track Delays
report.delays.append("Weather delay - rain from 14:00-16:00")
report.delays.append("Material delivery late by 2 hours")
3. Calculate Metrics
summary = reporter.calculate_summary(report)
print(f"Productivity: {summary['total_manhours']} man-hours")
Resources
- DDC Book: Chapter 4.1 - Site Data Collection
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
