Urban Calculator

What it does

When your agent uses it

• The user asks to calculate density
• Score walkability
• Determine parking requirements
• Analyze green space provision

Example prompts

• “/urban-calculator”

Requirements

• Python 3
• Pre-approved tools (allowed-tools): Bash(python *)

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

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

What it can do on your machine

Read from SKILL.md and the folder at commit 666327b. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Bash(python *)

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 6 files in scripts/ (Python), which the agent can run.

  Shell commands in SKILL.md call:

  • python

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Urban Calculator loads about 1.9k tokens when it runs, and up to ~6.1k if it reads all its reference files. Until then it costs about 133 tokens; SKILL.md has 531 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~133

When it runs · the whole SKILL.md, loaded when a task matches

~1.9k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~6.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from Abhinavbwj/Urban-Design-Skills-Claude at commit 666327b, republished under its MIT licence (© Abhinavbwj). 531 words, ~1,865 tokens.

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 *)

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

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

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

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"

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

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

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

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

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

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

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

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

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

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

# 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

{
  "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": 154.0,
    "gross_density_du_per_ha": 107.8,
    "population_density_persons_per_ha": 385.0
  }
}

© Abhinavbwj, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (scripts, references) in skills/urban-calculator of Abhinavbwj/Urban-Design-Skills-Claude.

• SKILL.md
• references/formulas.md
• scripts/block_optimizer.py
• scripts/density_calculator.py
• scripts/far_calculator.py
• scripts/green_space_analyzer.py
• scripts/parking_calculator.py
• scripts/walkability_scorer.py

Open the folder on GitHubat commit 666327b

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in Abhinavbwj/Urban-Design-Skills-Claude, which our catalogue first saw on October 7, 2026.

• NeverSight/learn-skills.devdata/skills-md/abhinavbwj/urban-design-skills-claude/urban-calculator