name	construction-takeoff
description	Automated construction quantity surveying from PDF plans using AI. Processes construction drawings, extracts quantities/materials, analyzes competitor solutions via Firecrawl, calculates costs, and generates Excel-based takeoff reports for stakeholder collaboration.

Construction Takeoff Agent

Name: construction-takeoff
Author: breverdbidder

Agentic AI system for automated construction quantity surveying from PDF construction plans.

Overview

The Construction Takeoff Agent is a specialized LangGraph orchestration that processes PDF construction plans (site plans, floor plans, elevations, details) to extract quantities, materials, and measurements. It integrates competitive intelligence via Firecrawl API and generates comprehensive Excel workbooks suitable for stakeholder collaboration.

Core Capabilities

1. PDF Plan Analysis

Processes construction plans using Claude's native vision capabilities
Supports multiple drawing types: site plans, floor plans, elevations, details
Extracts drawing scale, dimensions, annotations, and specifications
Handles multi-page PDFs with page-by-page analysis

2. Quantity Extraction

Identifies and quantifies construction materials
Categorizes items by CSI MasterFormat divisions:
- Earthwork (excavation, grading, fill)
- Concrete (slabs, footings, walls, columns)
- Masonry (brick, block, stone)
- Metals (structural steel, rebar)
- Wood & Plastics (framing, joists, decking)
- Finishes (drywall, paint, flooring, tile)
- Site Work (paving, curbs, landscaping, utilities)
- Mechanical/Electrical/Plumbing systems
Measures areas, linear dimensions, and volumes
Counts discrete items (doors, windows, fixtures)

3. Competitor Analysis (via Firecrawl)

Scrapes leading construction takeoff solutions:
- PlanSwift
- Bluebeam Revu
- On-Screen Takeoff
- STACK Construction Technologies
Extracts competitor features and automation capabilities
Identifies best practices and differentiators
Incorporates insights into report generation

4. Cost Estimation

Calculates material costs using Florida market unit prices (2025)
Estimates labor hours per construction task
Applies labor rates ($75/hour for Florida construction)
Provides detailed cost breakdown by category
Generates total project estimate (materials + labor)

5. Excel Report Generation

Creates multi-sheet workbook:
- Project Summary: Overview, cost totals, labor hours
- Detailed Takeoff: Line-item quantities with unit costs
- Materials List: Categorized materials with specifications
- Competitor Insights: Features and best practices discovered
Professional formatting with headers, colors, borders
Currency and number formatting
Auto-sized columns for readability

6. Supabase Integration

Logs all takeoff results to insights table
Category: spd_construction_takeoff
Stores project metadata, costs, report paths
Enables historical analysis and reporting

Workflow Stages

1. PDF Processing → Analyze construction plans with Claude Vision
2. Quantity Extraction → Structure quantities using AI
3. Competitor Analysis → Scrape competitors via Firecrawl
4. Cost Calculation → Apply unit costs and labor rates
5. Report Generation → Create Excel workbook
6. Supabase Logging → Store results for tracking

Usage

Via GitHub Actions (Recommended)

Trigger the workflow from GitHub Actions UI or API:

curl -X POST \
  -H "Authorization: token YOUR_GITHUB_TOKEN" \
  -H "Accept: application/vnd.github.v3+json" \
  https://api.github.com/repos/breverdbidder/spd-site-plan-dev/actions/workflows/construction_takeoff_workflow.yml/dispatches \
  -d '{
    "ref": "main",
    "inputs": {
      "pdf_url": "https://example.com/construction_plan.pdf",
      "project_name": "Bliss Palm Bay Phase 2",
      "project_id": "SPD-2025-003"
    }
  }'

Via Python API

from construction_takeoff_agent import run_construction_takeoff

result = run_construction_takeoff(
    pdf_path="/path/to/construction_plan.pdf",
    project_name="Bliss Palm Bay Phase 2",
    project_id="SPD-2025-003"
)

print(f"Total Cost: ${result['total_estimated_cost']:,.2f}")
print(f"Excel Report: {result['excel_path']}")

CLI Usage

python construction_takeoff_agent.py \
  /path/to/construction_plan.pdf \
  "Bliss Palm Bay Phase 2" \
  "SPD-2025-003"

Configuration

Environment Variables

Required:

ANTHROPIC_API_KEY - Claude API for PDF analysis and quantity extraction
SUPABASE_SERVICE_ROLE_KEY - Database logging

Optional:

FIRECRAWL_API_KEY - Competitor analysis (skipped if not provided)

Unit Cost Database

The agent includes Florida construction market unit costs (2025). Modify UNIT_COSTS dictionary in the agent file to update:

UNIT_COSTS = {
    "excavation": {"unit": "CY", "cost": 12.50, "labor_hours": 0.05},
    "concrete_slab": {"unit": "CY", "cost": 150.00, "labor_hours": 0.75},
    # ... add more items
}

Competitor Targets

Configure competitor sites to analyze in COMPETITOR_TARGETS:

COMPETITOR_TARGETS = [
    {
        "name": "PlanSwift",
        "url": "https://www.planswift.com",
        "focus": "Digital takeoff and estimating software"
    },
    # ... add more competitors
]

Output Format

Excel Workbook Structure

Sheet 1: Project Summary

Project metadata (name, ID, date, drawing type, scale)
Cost summary (materials, labor, total)

Sheet 2: Detailed Takeoff

Item	Quantity	Unit	Unit Cost	Total Cost	Labor Hours	Category
Excavation	250	CY	$12.50	$3,125.00	12.5	earthwork
Concrete Slab	50	CY	$150.00	$7,500.00	37.5	concrete

Sheet 3: Materials List

Material	Quantity	Unit	Category	Specification
3000 PSI Concrete	50	CY	concrete	Ready-mix

Sheet 4: Competitor Insights

Features by competitor
Best practices identified
Automation capabilities

Integration with API Mega Library

The agent references the API mega library located at:

Repository: breverdbidder/life-os
Path: docs/API_MEGA_LIBRARY.md
Contains 10,498+ APIs including construction, estimation, and automation tools

The agent can be extended with additional APIs from the mega library:

Construction APIs: Procore, Buildertrend, CoConstruct
Estimation APIs: HCSS HeavyBid, B2W Estimate
Document Processing: Adobe PDF Services, DocParser
Computer Vision: Google Cloud Vision, AWS Textract

Best Practices Cloned from Competitors

Based on Firecrawl analysis, the agent incorporates:

Auto-scaling from drawings (PlanSwift pattern)
Multi-trade categorization (Bluebeam approach)
Assembly-based costing (On-Screen Takeoff method)
Real-time collaboration (STACK model)
Cloud-based storage (Industry standard)

Performance Metrics

PDF Processing: ~30 seconds per page (Claude Vision)
Competitor Scraping: ~20 seconds per site (Firecrawl)
Cost Calculation: <5 seconds
Excel Generation: <10 seconds
Total Workflow: ~2-5 minutes for typical single-page plan

Limitations & Future Enhancements

Current Limitations

Manual PDF upload required (no automatic discovery)
Single drawing analysis (batch processing not yet implemented)
Static unit cost database (not market-integrated)
Limited to PDF format (no DWG/DXF CAD files)

Planned Enhancements

Integration with RSMeans cost database
CAD file format support (DWG, DXF, RVT)
Machine learning for quantity prediction
Historical project comparison
Multi-project batch processing
Real-time collaboration features
Mobile app for field verification

Cost Analysis

Per-Takeoff Costs

Claude API (PDF analysis): ~$0.15-0.30 per page
Firecrawl (competitor scraping): ~$0.03 per site
Supabase (logging): <$0.01
GitHub Actions (compute): Free tier

Total per takeoff: ~$0.20-0.50

ROI Calculation

Traditional manual takeoff: 4-8 hours @ $75/hour = $300-600 Automated takeoff: 5 minutes + $0.50 = ~$10-20 equivalent

Time savings: 95-98% Cost savings: 95-97%

Repository Structure

spd-site-plan-dev/
├── agents/
│   └── orchestrator/
│       └── construction_takeoff_agent.py    # Main agent
├── .github/
│   └── workflows/
│       └── construction_takeoff_workflow.yml # GitHub Actions
├── skills/
│   └── construction-takeoff/
│       └── SKILL.md                         # This file
├── reports/
│   └── takeoff_reports/                     # Generated Excel reports
└── docs/
    └── CONSTRUCTION_TAKEOFF.md              # Extended documentation

Supabase Schema

The agent logs to the insights table:

{
  "category": "spd_construction_takeoff",
  "insight_type": "takeoff_report",
  "insight_data": {
    "project_id": "SPD-2025-003",
    "project_name": "Bliss Palm Bay Phase 2",
    "drawing_type": "site_plan",
    "total_quantities": 45,
    "total_materials": 32,
    "total_cost": 125000.00,
    "labor_hours": 520.5,
    "competitors_analyzed": ["PlanSwift", "Bluebeam Revu"],
    "excel_report": "/tmp/spd_takeoff_reports/takeoff_SPD-2025-003_20251219_143022.xlsx",
    "status": "completed",
    "timestamp": "2025-12-19T14:30:22Z"
  }
}

Support & Troubleshooting

Common Issues

Issue: PDF processing fails with "invalid format" Solution: Ensure PDF is not password-protected or corrupted

Issue: Firecrawl returns 401 Unauthorized Solution: Verify FIRECRAWL_API_KEY environment variable is set

Issue: Unit costs seem inaccurate Solution: Update UNIT_COSTS dictionary with current market rates

Issue: Excel report missing competitor insights Solution: Verify Firecrawl API key and check rate limits

Debug Mode

Enable verbose logging:

import logging
logging.basicConfig(level=logging.DEBUG)

result = run_construction_takeoff(pdf_path, project_name)

Security Considerations

PDF files may contain sensitive project information
Store reports in secure locations
Rotate API keys regularly
Use Supabase Row Level Security (RLS) for insights table
Sanitize file paths to prevent directory traversal

License & Attribution

Agent: Everest Capital USA / BidDeed.AI
LangGraph: LangChain Inc.
Claude API: Anthropic
Firecrawl: Mendable AI
OpenPyXL: Open source (MIT)

Changelog

v1.0.0 (2025-12-19)

Initial release
PDF construction plan processing
Automated quantity extraction
Competitor analysis via Firecrawl
Excel report generation
Supabase integration
GitHub Actions workflow

Maintained by: Claude Sonnet 4.5 (AI Architect) Repository: github.com/breverdbidder/spd-site-plan-dev Stack: LangGraph + Anthropic Claude + Firecrawl + OpenPyXL + Supabase

Install Skill

SKILL.md