casualize-names

name	casualize-names
description	Convert formal names to casual versions for cold email personalization - first names, company names, and city names. Use when user asks to casualize names, make names friendly, or prepare lead data for emails.

Casualize Names Workflow

Goal

Convert formal names (first names, company names, cities) to casual, friendly versions suitable for cold email copy.

Scripts

• ./scripts/casualize_batch.py - Main script (all 3 fields at once)
• ./scripts/casualize_company_names_batch.py - Company names only
• ./scripts/casualize_first_names_batch.py - First names only
• ./scripts/casualize_city_names_batch.py - City names only

Quick Start

# Process all three fields at once (recommended, 3x faster)
python3 -u ./scripts/casualize_batch.py "GOOGLE_SHEET_URL"

# Re-process existing (overwrite)
python3 -u ./scripts/casualize_batch.py "GOOGLE_SHEET_URL" --overwrite

How It Works

1. Processes records in batches of 50
2. Uses 5 parallel workers
3. Claude converts all three fields in one API call
4. Batch updates Google Sheet with results
5. Only processes rows with emails

Performance: ~35 records/sec (3,000 records ≈ 90 seconds)

Casualization Rules

First Names

• Use common nicknames: "William" → "Will", "Jennifer" → "Jen"
• Keep original if no common nickname exists
• Keep it professional

Company Names

• Remove "The" at beginning
• Remove legal suffixes (LLC, Inc, Corp, Ltd)
• Remove generic words (Realty, Group, Solutions, Services)
• Keep core brand name
• Use "you guys" for overly generic names

Examples:

• "Keller Williams Realty Inc" → "Keller Williams"
• "The Teal Umbrella Family Dental Healthcare" → "Teal Umbrella"

City Names

• Use local nicknames: "San Francisco" → "SF", "Philadelphia" → "Philly"
• Keep original if no common nickname

Output

Creates three new columns:

• casual_first_name
• casual_company_name
• casual_city_name

Environment

ANTHROPIC_API_KEY=your_key

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Schema

Inputs

Name	Type	Required	Description
sheet_url	string	Yes	Google Sheet URL with lead data
overwrite	boolean	No	Re-process existing casualized names

Outputs

Name	Type	Description
sheet_url	string	Same sheet with casual_first_name, casual_company_name, casual_city_name columns added

Credentials

Name	Source
ANTHROPIC_API_KEY	.env

Composable With

Skills that chain well with this one: scrape-leads, gmaps-leads, instantly-campaigns

Cost

~35 records/sec, minimal API cost