urban-calculator

name	urban-calculator
description	Python computational tools for urban design metric calculations including density, FAR, walkability scoring, parking requirements, green space analysis, and block optimization. Use when the user asks to calculate density, compute FAR, score walkability, determine parking requirements, analyze green space provision, optimize block dimensions, run urban metrics, or perform any quantitative urban design calculation. Also use when precise numbers are needed for any urban design metric rather than rules of thumb.
allowed-tools	Bash(python *)

Urban Calculator

A suite of Python computational tools for precise urban design metric calculations. Each script is self-contained, accepts inputs via command-line arguments, and outputs both human-readable text and structured JSON.

Available Calculators

Script	Purpose	Key Inputs	Key Outputs
density_calculator.py	Population and dwelling density	Site area, FAR, unit sizes, efficiency	DU/ha, persons/ha, population
far_calculator.py	FAR and GFA optimization	Site area, coverage, floors, uses	FAR, GFA per use, total GFA
walkability_scorer.py	Walk Score estimation	Amenity distances, network connectivity	Score 0-100, category
parking_calculator.py	Parking requirements	Uses, areas, ratios, reductions	Total spaces, area needed
green_space_analyzer.py	Green space adequacy	Population, park areas, distances	Per capita m2, service coverage
block_optimizer.py	Block dimension optimization	Target FAR, height, coverage, daylight	Optimal block dimensions

Usage Instructions

All scripts are located in the scripts/ subdirectory relative to this skill. Run them with Python 3 via the command line. Every script supports a --json flag to output structured JSON instead of formatted text.

Density Calculator

Calculate population and dwelling density for a development site:

python scripts/density_calculator.py --site-area 20000 --far 2.5 --avg-unit-size 85 --efficiency 0.75 --household-size 2.5 --residential-pct 0.7 --streets-pct 0.30

Minimal example (uses defaults for optional parameters):

python scripts/density_calculator.py --site-area 15000 --far 3.0

JSON output:

python scripts/density_calculator.py --site-area 20000 --far 2.5 --json

FAR Calculator

Calculate Floor Area Ratio and Gross Floor Area by use:

python scripts/far_calculator.py --site-area 10000 --coverage 0.6 --floors 4,6,8 --use-split "res:60,com:25,civic:10,open:5"

With bonus FAR for affordable housing:

python scripts/far_calculator.py --site-area 10000 --coverage 0.6 --floors 6 --bonus-far 0.5

With explicit floor areas per zone:

python scripts/far_calculator.py --site-area 10000 --floor-areas "2000,3000,1500" --floors "4,6,8"

Walkability Scorer

Estimate a Walk Score based on amenity distances and intersection density:

python scripts/walkability_scorer.py --grocery 200 --restaurants 150 --shopping 400 --coffee 100 --parks 300 --schools 500 --intersection-density 150

Minimal example (unspecified amenities default to 9999m = not present):

python scripts/walkability_scorer.py --grocery 300 --parks 200

Parking Calculator

Determine parking requirements with transit and TDM reductions:

python scripts/parking_calculator.py --residential-units 200 --office-area 5000 --retail-area 2000 --transit-reduction 0.2 --shared-reduction 0.1 --space-type structured

Surface parking example:

python scripts/parking_calculator.py --residential-units 50 --space-type surface

Green Space Analyzer

Analyze green space provision against international standards:

python scripts/green_space_analyzer.py --population 5000 --parks "Central Park:8000:neighborhood,Pocket Plaza:400:pocket,River Walk:2000:linear" --standard who

JSON output with UN-Habitat standard:

python scripts/green_space_analyzer.py --population 12000 --parks "Main Park:15000:district,Local Green:1200:neighborhood" --standard un-habitat --json

Block Optimizer

Find optimal block dimensions for a target FAR:

python scripts/block_optimizer.py --target-far 2.5 --max-height 6 --building-depth 14 --min-courtyard 21 --daylight-angle 25

Higher density example:

python scripts/block_optimizer.py --target-far 4.0 --max-height 10 --max-coverage 0.7 --building-depth 16

Formula Reference

All formulas, worked examples, unit conversions, and standard assumptions are documented in references/formulas.md. Key formulas used across the calculators:

• FAR = Total GFA / Site Area
• Net Density (DU/ha) = Dwelling Units / Net Site Area (ha)
• Gross Density (DU/ha) = Dwelling Units / Gross Site Area including streets (ha)
• Population Density = Net Density x Household Size
• Walk Score = Weighted sum of distance-decay scores per amenity category, normalized to 0-100
• Parking Spaces = Sum of (use area x ratio) x (1 - transit reduction) x (1 - shared reduction) x (1 - TDM reduction)
• Green Space Per Capita = Total Green Space Area / Population

See references/formulas.md for the complete reference with worked examples.

Integration

Other skills in the Urban Design Skills can invoke these calculators to get precise numbers. The recommended integration pattern is:

1. From a design skill: After generating a site layout, call density_calculator.py and far_calculator.py with the computed areas to validate metrics.
2. From a masterplan skill: Use block_optimizer.py to determine block dimensions before laying out the street grid.
3. From an analysis skill: Run walkability_scorer.py and green_space_analyzer.py to evaluate design proposals against standards.
4. Chaining calculators: Use the --json flag to pipe outputs between scripts programmatically.

Example chain (compute density then check green space):

# Step 1: Calculate density to get population
python scripts/density_calculator.py --site-area 50000 --far 2.5 --json > density_output.json

# Step 2: Use the population estimate to check green space adequacy
python scripts/green_space_analyzer.py --population 3500 --parks "Park A:5000:neighborhood,Park B:800:pocket" --json

Output Formats

All scripts support two output modes:

1. Human-readable text (default): Formatted tables and summaries suitable for reports and presentations. Includes section headers, aligned columns, and contextual notes.

2. JSON (with --json flag): Structured data suitable for programmatic consumption, piping between scripts, and integration with other tools. All numeric values are provided as numbers (not strings), and all units are documented in the JSON keys.

Example JSON output structure (density calculator):

{
  "inputs": {
    "site_area_m2": 20000,
    "far": 2.5,
    "avg_unit_size_m2": 85,
    "efficiency": 0.75,
    "household_size": 2.5,
    "residential_pct": 0.7,
    "streets_pct": 0.30
  },
  "results": {
    "total_gfa_m2": 50000,
    "residential_gfa_m2": 35000,
    "net_internal_area_m2": 26250,
    "dwelling_units": 308,
    "population": 771,
    "net_density_du_per_ha":