casualize-names: Data & Analytics for AI Agents | OpenAgentSkill

Overview

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.

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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

Processes records in batches of 50
Uses 5 parallel workers
Claude converts all three fields in one API call
Batch updates Google Sheet with results
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

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

View source ↗

File metadata

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.

View original text

---
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

```bash
# 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
```

---

## 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

Review the source

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
SKILL.md contains a minor typo: 'overly generic name' should likely be 'overly generic names'.
The scripts are not fully shown in the excerpt, but the provided code appears functional and follows standard practices.
Low GitHub adoption signal
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 16 GitHub stars
Stars/forks activity: 16 stars, 6 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

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Source & usage notes

Indexed

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: aiagentwithdhruv/skills
License: MIT
Version: 1.0.0
Last GitHub push: Aug 27, 2026
Registry updated: Sep 1, 2026
Instruction path: casualize-names/SKILL.md

Version reported in registry metadata; check source releases before relying on it.

Quality

59/100

Promising

Trust

53/100

Do not auto-install

Agent access

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Open install API LLM text format Open manifest Auto-resolve Plan

More details

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}

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Source: aiagentwithdhruv/skills
Indexed by: OpenAgentSkill community index

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