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daily-report-generator

Automatically generate daily construction reports from field data, worker inputs, weather, and progress photos. Creates professional PDF reports.

Install / Use

npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill daily-report-generator

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

91/100

Category

Automation

Supported Platforms

Universal

Our assessment of daily-report-generator

daily-report-generator scores 91/100 on our quality scale, 1190th of 2,904 Automation skills we index (top 41%).

Its SKILL.md is 20 KB long, well organised into 13 sections with 6 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.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
11/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated about 2 months ago, so daily-report-generator 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-report-generator compared with similar skills

All 4 of these similar skills score higher than daily-report-generator; compare them before choosing.

SkillScoreStarsUpdatedFormat
daily-report-generator (this skill)by datadrivenconstruction9133356d agoSKILL.md
Agent-Reachby Panniantong10098.3k2d agoCLAUDE.md
headroomby headroomlabs-ai10075.5ktodayCLAUDE.md
Scraplingby D4Vinci10088.2ktodayMCP Server
crawl4aiby unclecode10085.7k2d agoMCP Server

Frequently asked questions

How do I install daily-report-generator?
Run npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill daily-report-generator. The install tabs above show the steps for each supported agent.
Which AI agents does daily-report-generator 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-report-generator 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-report-generator still maintained?
The repository was last updated about 2 months ago, so daily-report-generator is actively maintained.

name: "daily-report-generator" description: "Automatically generate daily construction reports from field data, worker inputs, weather, and progress photos. Creates professional PDF reports." homepage: "https://datadrivenconstruction.io" metadata: {"openclaw": {"emoji": "🏗️", "os": ["darwin", "linux", "win32"], "homepage": "https://datadrivenconstruction.io", "requires": {"bins": ["python3"]}}}

Daily Report Generator for Construction Sites

Automate the creation of comprehensive daily construction reports by aggregating data from multiple sources into professional documentation.

Business Case

Problem: Site managers spend 45-60 minutes daily on:

  • Collecting information from foremen
  • Checking weather conditions
  • Compiling worker counts and hours
  • Writing narrative summaries
  • Formatting and distributing reports

Solution: Automated system that:

  • Pulls data from Google Sheets/project database
  • Integrates weather API data
  • Aggregates worker timesheets
  • Generates professional PDF reports
  • Distributes to stakeholders automatically

ROI: 80% reduction in daily reporting time (45 min → 9 min for review)

Report Structure

┌──────────────────────────────────────────────────────────────────────┐
│                    DAILY CONSTRUCTION REPORT                          │
│                                                                       │
│  Project: ЖК Солнечный, Корпус 2          Date: 24.01.2026           │
│  Report #: DCR-2026-024                   Weather: ☁️ -5°C           │
├──────────────────────────────────────────────────────────────────────┤
│                                                                       │
│  1. WEATHER CONDITIONS                                                │
│  ┌────────────┬────────────┬────────────┬────────────┐               │
│  │ Morning    │ Afternoon  │ Evening    │ Impact     │               │
│  │ -8°C ☀️    │ -5°C ☁️    │ -7°C 🌙    │ Normal     │               │
│  └────────────┴────────────┴────────────┴────────────┘               │
│                                                                       │
│  2. WORKFORCE                                                         │
│  ┌────────────────────────────────────────────────────┐              │
│  │ Category          │ Planned │ Actual │ Hours      │              │
│  ├────────────────────────────────────────────────────┤              │
│  │ GC Supervision    │    3    │   3    │    27      │              │
│  │ Electrical        │   12    │  11    │    88      │              │
│  │ Plumbing          │    8    │   8    │    64      │              │
│  │ HVAC              │    6    │   6    │    48      │              │
│  │ TOTAL             │   29    │  28    │   227      │              │
│  └────────────────────────────────────────────────────┘              │
│                                                                       │
│  3. WORK COMPLETED TODAY                                              │
│  • Electrical: Completed rough-in floors 5-6                         │
│  • Plumbing: Installed risers section A                              │
│  • HVAC: Ductwork installation 60% complete                          │
│                                                                       │
│  4. WORK PLANNED FOR TOMORROW                                         │
│  • Electrical: Begin rough-in floor 7                                │
│  • Plumbing: Continue risers section B                               │
│  • HVAC: Complete ductwork, begin testing                            │
│                                                                       │
│  5. ISSUES / DELAYS                                                   │
│  • Material delay: Electrical panels (ETA: 26.01)                    │
│  • Weather: Expected snow may delay exterior work                    │
│                                                                       │
│  6. SAFETY                                                            │
│  ✅ No incidents                                                      │
│  ✅ Toolbox talk completed: Fall protection                          │
│                                                                       │
│  7. PHOTOS                                                            │
│  [Photo 1: Floor 5 electrical]  [Photo 2: Riser installation]        │
│                                                                       │
│  ─────────────────────────────────────────────────────────────────   │
│  Prepared by: Иван Петров, Site Manager                              │
│  Approved by: ___________________                                     │
│  Distribution: Owner, Architect, PM                                   │
└──────────────────────────────────────────────────────────────────────┘

Python Implementation

import pandas as pd
from datetime import datetime, date
from typing import Optional, List, Dict
import requests
from reportlab.lib import colors
from reportlab.lib.pagesizes import A4
from reportlab.platypus import SimpleDocTemplate, Table, TableStyle, Paragraph, Spacer, Image
from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
from reportlab.lib.units import cm
import os

class DailyReportGenerator:
    """Generate professional daily construction reports"""

    def __init__(self, config: dict):
        self.config = config
        self.weather_api_key = config.get('weather_api_key')
        self.project_name = config.get('project_name')
        self.report_date = config.get('report_date', date.today())

    def get_weather_data(self, location: str) -> dict:
        """Fetch weather data from API"""
        if not self.weather_api_key:
            return self._mock_weather()

        url = f"https://api.openweathermap.org/data/2.5/weather"
        params = {
            'q': location,
            'appid': self.weather_api_key,
            'units': 'metric',
            'lang': 'ru'
        }

        response = requests.get(url, params=params)
        if response.status_code == 200:
            data = response.json()
            return {
                'temp': round(data['main']['temp']),
                'description': data['weather'][0]['description'],
                'humidity': data['main']['humidity'],
                'wind_speed': round(data['wind']['speed']),
                'icon': self._get_weather_icon(data['weather'][0]['main'])
            }
        return self._mock_weather()

    def _get_weather_icon(self, condition: str) -> str:
        icons = {
            'Clear': '☀️',
            'Clouds': '☁️',
            'Rain': '🌧️',
            'Snow': '❄️',
            'Thunderstorm': '⛈️',
            'Mist': '🌫️'
        }
        return icons.get(condition, '🌤️')

    def _mock_weather(self) -> dict:
        return {
            'temp': -5,
            'description': 'облачно',
            'humidity': 65,
            'wind_speed': 3,
            'icon': '☁️'
        }

    def get_workforce_data(self, source: pd.DataFrame) -> dict:
        """Aggregate workforce data from timesheet"""
        # Expected columns: trade, worker_name, hours_worked, planned_hours

        summary = source.groupby('trade').agg({
            'worker_name': 'count',
            'hours_worked': 'sum',
            'planned_hours': 'sum'
        }).reset_index()

        summary.columns = ['trade', 'actual_count', 'actual_hours', 'planned_hours']

        # Calculate planned count (assuming 8-hour shifts)
        summary['planned_count'] = (summary['planned_hours'] / 8).astype(int)

        return {
            'trades': summary.to_dict('records'),
            'total_workers': summary['actual_count'].sum(),
            'total_hours': summary['actual_hours'].sum(),
            'total_planned': summary['planned_count'].sum()
        }

    def get_work_completed(self, tasks: pd.DataFrame) -> List[dict]:
        """Extract completed work from task system"""
        # Filter completed tasks for today
        completed = tasks[
            (tasks['date'] == self.report_date.strftime('%d.%m.%Y')) &
            (tasks['status'].isin(['Completed', 'Partial']))
        ]

        work_items = []
        for _, row in completed.iterrows():
            work_items.append({
                'trade': row['trade'],
                'description': row['description'],
                'status': row['status'],
                'notes': row.get('notes', '')
            })

        return work_items

    def get_work_planned(self, tasks: pd.DataFrame) -> List[dict]:
        """Get planned work for tomorrow"""
        tomorrow = self.report_date + pd.Timedelta(days=1)

        planned = tasks[
            tasks['date'] == tomorrow.strftime('%d.%m.%Y')
        ]

        work_items = []
        for _, row in planned.iterrows():
            work_items.append({
                'trade': row['trade'],
                'description': row['description'],
                'priority': row.get('priority', 'Medium')
            })

        return work_items

    def get_issues(self, issues_log: pd.DataFrame) -> List[dict]:
        """Get active issues and delays"""
        active = issues_log[
            (issues_log['status'] == 'Open') |
            (issues_log['date_reported'] == self.report_date.strftime('%d.%m.%Y'))
        ]

        return active[['category', 'description', 'impact', 'resolution_date']].to_dict('records')

    def get_safety_data(self, safety_log: pd.DataFrame) -> dict:
        """Get safety information for the day"""
        today_incidents = safety_log[
            safety_log['date'] == self.report_date.strftime('%d.%m.%Y')
        ]

        return {
            'incidents': len(today_incidents[today_incidents['type'] == 'Incident']),
            'near_misses': len(today_incidents[today_incidents['type'] == 'Near Miss']),
            'toolbox_talk': today_incidents[
                today_incidents['type'] == 'Toolbox Talk'
            ]['topic'].tolist(),
            'observations': today_incidents[
                today_incidents['type'] == 'Observation'
            ]['description'].tolist()
        }

    def generate_report(self, data: dict, output_path: str) -> str:
        """Generate PDF report"""

        doc = SimpleDocTemplate(
            output_path,
            pagesize=A4,
            rightMargin=2*cm,
            leftMargin=2*cm,
            topMargin=2*cm,
            bottomMargin=2*cm
        )

        styles = getSampleStyleSheet()
        title_style = ParagraphStyle(
            'Title',
            parent=styles['Heading1'],
            fontSize=16,
            alignment=1,
            spaceAfter=12
        )
        heading_style = ParagraphStyle(
            'Heading',
            parent=styles['Heading2'],
            fontSize=12,
            spaceBefore=12,
            spaceAfter=6
        )

        elements = []

        # Title
        elements.append(Paragraph(
            f"DAILY CONSTRUCTION REPORT",
            title_style
        ))

        # Header info
        header_data = [
            ['Project:', self.project_name, 'Date:', self.report_date.strftime('%d.%m.%Y')],
            ['Report #:', data.get('report_number', 'DCR-001'), 'Weather:', f"{data['weather']['icon']} {data['weather']['temp']}°C"]
        ]
        header_table = Table(header_data, colWidths=[3*cm, 6*cm, 3*cm, 4*cm])
        header_table.setStyle(TableStyle([
            ('FONTNAME', (0, 0), (-1, -1), 'Helvetica'),
            ('FONTSIZE', (0, 0), (-1, -1), 10),
            ('FONTNAME', (0, 0), (0, -1), 'Helvetica-Bold'),
            ('FONTNAME', (2, 0), (2, -1), 'Helvetica-Bold'),
        ]))
        elements.append(header_table)
        elements.append(Spacer(1, 12))

        # Weather section
        elements.append(Paragraph("1. WEATHER CONDITIONS", heading_style))
        weather = data['weather']
        weather_text = f"""
        Temperature: {weather['temp']}°C | Humidity: {weat

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars333
CategoryAutomation
Updated1mo ago
Forks82

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions