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DDC Skills Collection for AI Coding Assistants

AI Tools for Construction Company Automation

"ETL: transitioning from manual to automated management allows companies to process data without constant human intervention." — Data-Driven Construction, Chapter 4.2

Works with any AI coding assistant:

Claude Code · Cursor · GitHub Copilot · Gemini Code Assist · Cody · Continue · OpenCode · Aider

What is this?

A collection of 172 ready-to-use skills for automating construction company processes with AI.

flowchart LR
    subgraph INPUT["📥 YOUR DATA"]
        A1[Excel Estimates]
        A2[Revit/IFC Models]
        A3[Site Photos]
        A4[PDF Documents]
    end

    subgraph DDC["⚙️ DDC SKILLS"]
        B1[ETL Pipeline]
        B2[IFC Parser]
        B3[AI Analysis]
        B4[Document OCR]
    end

    subgraph OUTPUT["📤 RESULTS"]
        C1[Auto Reports]
        C2[Auto Estimates]
        C3[Progress Tracking]
        C4[Searchable Data]
    end

    A1 --> B1 --> C1
    A2 --> B2 --> C2
    A3 --> B3 --> C3
    A4 --> B4 --> C4

    style INPUT fill:#e1f5fe
    style DDC fill:#fff3e0
    style OUTPUT fill:#e8f5e9
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Who is this for?

Role What you get Start with
Executive Understanding how to automate your company GETTING_STARTED.md
Estimator Automated estimate creation estimate-builder, semantic-search-cwicr
PM / Superintendent Automatic reports n8n-daily-report, n8n-photo-report
IT / Developer Ready Python scripts and APIs Any skill from 2_DDC_Book/

How does it work?

flowchart LR
    subgraph S1["STEP 1<br/>1-2 days"]
        A[🔍 Find<br/>Data Silos]
    end

    subgraph S2["STEP 2<br/>1 week"]
        B[🔗 Connect<br/>Data Sources]
    end

    subgraph S3["STEP 3<br/>2-4 weeks"]
        C[⚡ Create<br/>ETL Pipelines]
    end

    subgraph S4["STEP 4<br/>Ongoing"]
        D[📈 Scale<br/>Add AI/ML]
    end

    A --> B --> C --> D

    A1[data-silo-detection] -.-> A
    B1[etl-pipeline<br/>data-type-classifier] -.-> B
    C1[n8n-daily-report<br/>n8n-photo-report] -.-> C
    D1[cost-prediction<br/>ML models] -.-> D

    style S1 fill:#ffebee
    style S2 fill:#fff3e0
    style S3 fill:#e8f5e9
    style S4 fill:#e3f2fd
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Collection Structure

mindmap
  root((DDC Skills<br/>172 skills))
    1_DDC_Toolkit
      CWICR Database
        55,719 work items
        9 languages
      CAD Converters
        Revit → Excel
        IFC → Excel
        DWG → Excel
      Analytics
        KPI Dashboard
        Cost Analysis
    2_DDC_Book
      Part I: Data Evolution
      Part II: Data Types
      Part III: Estimation
      Part IV: Analytics & ML
      Part V: Threats & Strategy
    3_DDC_Insights
      n8n Workflows
        Daily Reports
        Photo Reports
      Integration Patterns
    4_DDC_Curated
      Document Generation
        PDF
        Excel
      Quality Assurance
      Security
    5_DDC_Innovative
      AI/ML Skills
        Defect Detection
        Risk Assessment
      IoT & Sensors
        Material Tracking
        Site Monitoring
      Advanced BIM
        Digital Twin
        Clash Detection
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Data Types in Construction

flowchart TB
    subgraph STRUCTURED["📊 STRUCTURED"]
        S1[Excel]
        S2[SQL Database]
        S3[CSV]
    end

    subgraph SEMI["📋 SEMI-STRUCTURED"]
        M1[IFC/BIM]
        M2[JSON]
        M3[XML]
    end

    subgraph UNSTRUCTURED["📄 UNSTRUCTURED"]
        U1[PDF]
        U2[Photos]
        U3[Scans]
    end

    STRUCTURED -->|SQL queries| DB[(Central<br/>Database)]
    SEMI -->|Parsing| DB
    UNSTRUCTURED -->|AI/OCR| DB

    DB --> AUTO[🤖 Automation]

    style STRUCTURED fill:#c8e6c9
    style SEMI fill:#fff9c4
    style UNSTRUCTURED fill:#ffcdd2
    style DB fill:#e1f5fe
    style AUTO fill:#f3e5f5
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Top 10 Skills to Start

# Skill What it does Time savings
1 semantic-search-cwicr Search 55,719 work items database 99% (15 min → 10 sec)
2 etl-pipeline Automated Excel/PDF processing 80%
3 estimate-builder Build estimates from data 87%
4 n8n-daily-report Automated daily reports 92%
5 data-silo-detection Find isolated data sources -
6 ifc-to-excel Extract quantities from BIM 90%
7 n8n-photo-report AI-powered site photo analysis 83%
8 cost-prediction ML cost forecasting -
9 schedule-delay-analyzer Schedule variance analysis 87%
10 kpi-dashboard Project KPI dashboard 75%

Quick Start

1. Installation

pip install pandas openpyxl ifcopenshell pdfplumber qdrant-client

2. Example: Search Work Items

# Instead of 15 minutes searching manuals → 10 seconds

from qdrant_client import QdrantClient

client = QdrantClient("localhost", port=6333)
results = client.search(
    collection_name="ddc_cwicr_en",
    query_vector=get_embedding("concrete foundation pour"),
    limit=5
)

# Result:
# [{'code': '03.30.00', 'description': 'Concrete works - foundations', 'unit': 'm³'}]

3. Example: ETL Pipeline

# Automatic processing of all Excel files from folder

import pandas as pd
from pathlib import Path

# Extract
all_data = [pd.read_excel(f) for f in Path("./estimates/").glob("*.xlsx")]
df = pd.concat(all_data)

# Transform
df['Total'] = df['Quantity'] * df['Unit_Price']
summary = df.groupby('Category')['Total'].sum()

# Load
summary.to_excel("summary_report.xlsx")

4. Example: Automated Report (n8n)

flowchart LR
    A[⏰ Trigger<br/>5:00 PM daily] --> B[📊 Get Data<br/>Excel + Weather API]
    B --> C[⚙️ Process<br/>Aggregate & Format]
    C --> D[📄 Generate<br/>PDF Report]
    D --> E[📧 Send<br/>Email to Team]

    style A fill:#fff3e0
    style E fill:#e8f5e9
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Documentation

Document Description Audience
GETTING_STARTED.md Step-by-step automation guide Executives, beginners
OPTIMIZER_GUIDE.md How to work effectively with Claude Developers
IMPROVEMENT_ROADMAP.md Collection development plan Contributors

Folder Structure

DDC_Skills/
│
├── 1_DDC_Toolkit/              ← Production tools (85 skills)
│   ├── CWICR-Database/         ← 55,719 work items database
│   ├── CAD-Converters/         ← Revit/IFC/DWG → Excel
│   └── ...
│
├── 2_DDC_Book/                 ← Skills from the book (50 skills)
│   ├── 1.1-Data-Evolution/     ← Digital maturity assessment
│   ├── 1.2-Data-Silos-Integration/  ← Find & connect data sources
│   ├── 3.1-Cost-Estimation/    ← Build estimates from data
│   ├── 4.2-ETL-Automation/     ← Automate data pipelines
│   └── ...
│
├── 3_DDC_Insights/             ← Practical workflows (10 skills)
│   ├── Automation-Workflows/   ← n8n automation
│   ├── AI-Agents/              ← Multi-agent systems (2026)
│   ├── Field-Automation/       ← Telegram bot, voice reports
│   └── Open-Data-Transparency/ ← Uberization readiness
│
├── 4_DDC_Curated/              ← External skills (5 skills)
│   ├── Document-Generation/    ← PDF/Excel generation
│   └── Quality-Assurance/      ← Quality checks
│
├── 5_DDC_Innovative/           ← Advanced AI/ML skills (22 skills)
│   ├── defect-detection-ai/    ← Computer vision for defects
│   ├── digital-twin-sync/      ← Real-time BIM sync
│   └── ...
│
├── Books/                      ← Free book downloads (9 languages)
├── GETTING_STARTED.md          ← START HERE
└── README.md                   ← You are here

ROI of Automation

pie title Time Savings by Process
    "Estimates (87%)" : 87
    "Daily Reports (92%)" : 92
    "Budget Tracking (87%)" : 87
    "Rate Lookup (99%)" : 99
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Example Use Cases

Process Before After
Create estimate 2 days manual work 2 hours with ETL
Daily report 2 hours collecting data 10 min auto-generated
Find work item rate 15 min searching manuals 10 sec semantic search
Budget variance check Weekly manual review Real-time alerts
IFC quantity takeoff Manual measurement Automatic extraction
Subcontractor comparison Spreadsheet analysis AI-powered matching
Site photo documentation Manual sorting & tagging CV auto-classification
Schedule delay detection Monthly review meetings Predictive alerts
Document classification Manual filing NLP auto-categorization
Cost forecasting Expert intuition ML prediction models

These are just a few examples. See GETTING_STARTED.md for complete automation scenarios.

About the Book

DDC Book

"Data-Driven Construction" by Artem Boiko

The methodology behind this skills collection. In 2025, the book was downloaded by 10,000+ professionals from construction companies worldwide.

What's inside:

  • Data types in construction (structured, semi-structured, unstructured)
  • How to detect and eliminate data silos
  • ETL pipelines for construction automation
  • Machine learning for cost and schedule prediction
  • Digital transformation strategy

Available in 9 languages: English, German, Spanish, French, Ukrainian, Russian, Polish, Czech, Portuguese

ISBN: 978-3-9826255-9-1

Download Free (All Languages)

Resources

Resource Link
Book (All Languages) https://datadrivenconstruction.io/books/
Website https://datadrivenconstruction.io
CWICR Demo https://openconstructionestimate.com
GitHub https://github.com/datadrivenconstruction
CWICR Database https://github.com/datadrivenconstruction/OpenConstructionEstimate-DDC-CWICR
CAD2Data Pipeline https://github.com/datadrivenconstruction/cad2data-Revit-IFC-DWG-DGN-pipeline-with-conversion-validation-qto

License

  • CWICR Database: CC BY 4.0
  • DDC Tools: MIT License
  • Skills: MIT License

Start automation today → GETTING_STARTED.md

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