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Skill119 repo starsupdated 2d ago

architectural-drawing-parser

The architectural-drawing-parser extracts structured building data from architectural drawings, floor plans, and code compliance documents using Claude's vision capabilities. It returns normalized JSON containing IBC occupancy and construction types, sprinkler system details, building dimensions, unit breakdowns, egress data, and floor plan elements. Use this skill when converting professional architectural images into machine-readable data for downstream 3D modeling, code validation workflows, or building analysis automation.

Install in Claude Code
Copy
git clone --depth 1 https://github.com/TerminalSkills/skills /tmp/architectural-drawing-parser && cp -r /tmp/architectural-drawing-parser/skills/architectural-drawing-parser ~/.claude/skills/architectural-drawing-parser
Then start a new Claude Code session; the skill loads automatically.

SKILL.md

# Architectural Drawing Parser

## Overview

Vision AI pipeline to extract structured building data from architectural drawings, floor plans, and IBC/IRC code compliance documents. Uses Claude's vision capabilities to read and interpret professional drawings, returning a normalized JSON object suitable for downstream 3D modeling or code validation workflows.

Supports IBC occupancy types (A-1 through U), construction types (I-A through V-B), sprinkler systems (NFPA 13/13R/13D), building dimensions, unit breakdowns, egress data, and floor plan elements (rooms, walls, doors, windows).

## Instructions

### Supported Drawing Types

| Drawing Type | What Is Extracted |
|---|---|
| IBC/IRC code compliance drawings | Occupancy, construction type, heights, stories, areas, egress, units |
| Floor plans (unit-level) | Rooms, dimensions, wall layouts, door/window positions |
| Site plans | Building footprint, setbacks, parking |
| Building area analysis tables | Unit types, SF per unit, occupant loads, travel distances |

### Output Data Structure

The parser returns a `BuildingData` JSON object with these fields:

- **occupancy** -- IBC occupancy type (e.g., "R-2", "A-2", "B")
- **constructionType** -- IBC construction type (e.g., "V-B", "I-A")
- **sprinklerSystem** -- "NFPA 13", "NFPA 13R", "NFPA 13D", or "None"
- **stories** -- `{ permitted, actual }`
- **height** -- `{ permitted: { feet, meters }, actual: { feet, meters } }`
- **totalBuildingArea** -- `{ sqft, sqm }`
- **units** -- Array of `{ name, area: { sqft, sqm }, occupantLoad, loadFactor, count }`
- **travelDistances** -- Array of `{ floor, maximum: { feet, meters } }`
- **scale** -- Scale notation string (e.g., `1/16" = 1'-0"`)
- **rooms** -- Array of `{ name, type, estimatedArea, dimensions }` (floor plans only)

### Parsing Approach

1. Send the drawing image to Claude's vision API with a structured extraction prompt
2. Request all building data as a single JSON object
3. Convert all areas to both sqft and sqm (1 sqft = 0.0929 sqm)
4. Convert all distances to both feet and meters (1 foot = 0.3048 m)
5. Parse the JSON from the response text

### Best Practices

- Use 150 DPI or higher for scanned drawings
- JPEG or PNG format; convert PDFs to images first (`pdftoppm -jpeg -r 150 drawing.pdf output`)
- Process multi-sheet PDFs one page at a time, then merge results
- Always verify extracted data against the source before structural calculations

## Examples

### Example 1: Parsing a Floor Plan PDF

A developer receives a scanned floor plan of a 2-bedroom apartment unit and needs room dimensions for a renovation estimate.

```
Input: apartment_unit_plan.jpg (scanned at 200 DPI, 1/4" = 1'-0" scale)

Extracted JSON:
{
  "rooms": [
    { "name": "Living Room", "type": "living", "estimatedArea": { "sqft": 240, "sqm": 22.3 }, "dimensions": { "width": 16, "depth": 15, "units": "feet" } },
    { "name": "Kitchen", "type": "kitchen", "estimatedArea": { "sqft": 120, "sqm": 11.1 }, "dimensions": { "width": 12, "depth": 10, "units": "feet" } },
    { "name": "Master Bedroom", "type": "bedroom", "estimatedArea": { "sqft": 168, "sqm": 15.6 }, "dimensions": { "width": 14, "depth": 12, "units": "feet" } },
    { "name": "Bedroom 2", "type": "bedroom", "estimatedArea": { "sqft": 132, "sqm": 12.3 }, "dimensions": { "width": 12, "depth": 11, "units": "feet" } },
    { "name": "Bathroom", "type": "bathroom", "estimatedArea": { "sqft": 48, "sqm": 4.5 }, "dimensions": { "width": 8, "depth": 6, "units": "feet" } }
  ],
  "scale": "1/4\" = 1'-0\""
}
```

The developer uses the room dimensions to calculate material quantities for flooring (708 sqft total) and wall paint coverage.

### Example 2: Extracting Building Data from an IBC Compliance Drawing

An architect submits a code compliance sheet for a 3-story apartment building. The parser extracts all building classification and egress data.

```
Input: ibc_compliance_sheet.jpg (building area analysis table + egress diagram)

Extracted JSON:
{
  "occupancy": "R-2",
  "constructionType": "V-B",
  "sprinklerSystem": "NFPA 13",
  "stories": { "permitted": 4, "actual": 3 },
  "height": {
    "permitted": { "feet": 60, "meters": 18.29 },
    "actual": { "feet": 35, "meters": 10.67 }
  },
  "totalBuildingArea": { "sqft": 8910, "sqm": 827.9 },
  "units": [
    { "name": "Type A", "area": { "sqft": 834, "sqm": 77.5 }, "occupantLoad": 5, "loadFactor": "1/200 SF", "count": 6 },
    { "name": "Type B", "area": { "sqft": 645, "sqm": 59.9 }, "occupantLoad": 4, "loadFactor": "1/200 SF", "count": 6 }
  ],
  "travelDistances": [
    { "floor": "Level 1", "maximum": { "feet": 66, "meters": 20.1 } },
    { "floor": "Level 2", "maximum": { "feet": 66, "meters": 20.1 } },
    { "floor": "Level 3", "maximum": { "feet": 66, "meters": 20.1 } }
  ]
}
```

This data feeds into the `ibc-building-codes` skill for compliance validation and the `spec-to-3d` skill for 3D model generation.

## Guidelines

- Accuracy depends on drawing quality and image resolution; low-res scans may produce incorrect dimensions
- Very small text (title blocks, fine notes) may be misread -- zoom in for detail drawings
- Complex overlapping hatching or linework may confuse room detection
- Proprietary symbols or non-standard abbreviations may not be recognized
- Always treat extracted data as an estimate; verify critical measurements manually
- For multi-sheet sets, parse each sheet separately and merge the structured data
- The parser works best with US-standard architectural drawings; metric-only drawings may need prompt adjustments