DDC_Skills_for_AI_Agents_in_Construction

DDC Skills Collection for AI Coding Assistants

AI Tools for Construction Company Automation

Works with any AI coding assistant:

What is this?

A collection of 238 skills for automating construction company processes with AI coding assistants.

What is a “Skill”?

A skill is a SKILL.md file — structured instructions that an AI coding assistant can read and execute. Each skill describes a specific task: what problem it solves, what code to generate, and what tools are needed. You open a skill folder in your AI assistant, and it helps you implement the described functionality.

Collection Structure

Skills are organized by source and complexity level:

Where to Start

If you manage or lead a construction company:

Step 1. Read GETTING_STARTED.md — a non-technical overview of what can be automated and how to prioritize.

Step 2. Download the Data-Driven Construction book (free, 31 languages) — it explains the methodology behind these skills: how to assess your company’s data maturity, identify bottlenecks, and plan digital transformation.

Step 3. Identify your biggest pain point in the table below and start with the corresponding skill.

If you are a developer or IT lead:

Step 1. Install prerequisites (see Prerequisites).

Step 2. Pick a skill from the table below, open its folder in your AI assistant, and follow the SKILL.md.

Step 3. Adapt the generated code to your data and deploy.

What Can You Automate?

Examples of common problems and which skills address them:

This is a selection of examples. The full collection contains 221 skills covering estimation, reporting, BIM, document processing, analytics, and more.

How to Use a Skill

1. Clone this repository
   git clone https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction.git

2. Open a skill folder in your AI assistant
   cd DDC_Skills_for_AI_Agents_in_Construction/1_DDC_Toolkit/CWICR-Database/semantic-search-cwicr/

3. The assistant reads SKILL.md and generates the code for you

4. Review, adapt to your data, and run

Example: ETL Pipeline

# Automatic processing of all Excel files from a 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")

Implementation Path

A typical automation project follows these stages. You don’t need to do all of them — start with what solves your most pressing problem.

Each stage builds on the previous one, but you can enter at any point depending on your current state.

How Does It Work?

Each step in the implementation path corresponds to specific skills and tools:

Data Types in Construction

Construction data comes in three forms. Each requires a different processing approach, and each has corresponding skills:

Prerequisites

Optional for advanced skills:

• Docker (for n8n workflows)
• PostgreSQL or SQLite (for database skills)
• OpenAI API key (for LLM-based skills)

Installation

pip install pandas openpyxl ifcopenshell pdfplumber

Data Flow in Construction

Skills cover the typical data pipeline: from raw input files to processed, actionable outputs.

Construction data comes in three forms. Each requires a different processing approach:

Folder Structure

DDC_Skills/
│
├── 1_DDC_Toolkit/              ← Production tools (85 skills)
│   ├── CWICR-Database/         ← 8 national bases + 30 markets database
│   ├── CAD-Converters/         ← Revit/IFC/DWG → Excel
│   └── ...
│
├── 2_DDC_Book/                 ← Skills from the book (67 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 (20 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 (20 skills)
│   ├── Document-Generation/    ← PDF/Excel/DOCX/PPTX generation
│   └── Quality-Assurance/      ← Quality checks
│
├── 5_DDC_Innovative/           ← Advanced AI/ML skills (29 skills)
│   ├── defect-detection-ai/    ← Computer vision for defects
│   ├── digital-twin-sync/      ← Real-time BIM sync
│   └── ...
│
├── Books/                      ← Free book downloads (31 languages)
├── GETTING_STARTED.md          ← START HERE
└── README.md                   ← You are here

Documentation

Potential Time Savings

Automation results vary depending on company size, data quality, and implementation effort:

Results depend on data preparation and workflow complexity. See GETTING_STARTED.md for implementation guidance.

About the Book

The majority of skills are based on the book “Data-Driven Construction” — a methodology for digital transformation in construction. The book explains the reasoning behind each skill category: why data silos matter, how to classify your data, and what to automate first.

Book structure maps to skills: Part I — Data landscape assessment → 2_DDC_Book/1.1-*, 1.2-* Part II — Data types and classification → 2_DDC_Book/2.1-* through 2.6-* Part III — Estimation and scheduling → 2_DDC_Book/3.1-* through 3.3-* Part IV — Analytics and ML → 2_DDC_Book/4.1-* through 4.5-* Part V — Threats and long-term strategy → 2_DDC_Book/5.* Download Free in 31 Languages →

Resources

Support the Project

If you find these tools useful, please give the repository a star — it helps others discover these resources.

Related repositories:

Contributing

Contributions are welcome:

• Report issues — bugs, unclear documentation, broken links
• Suggest skills — describe the automation you need
• Submit PRs — new skills, improvements, translations

Each skill should include a SKILL.md with clear instructions and working code examples.

License

• CWICR Database: CC BY-NC 4.0 (non-commercial; separate DDC commercial license)
• DDC Tools: MIT License
• Skills: MIT License

Trademarks

All product names, logos, and brands mentioned in this repository are property of their respective owners. All company, product and service names used are for identification purposes only. Use of these names, logos, and brands does not imply endorsement.

• IFC is an open standard by buildingSMART International
• File format references (RVT, DWG, DGN, NWD, etc.) are used for technical interoperability purposes only

Start here → GETTING_STARTED.md