pipeworx-genderize
Predict the likely gender associated with a first name — with optional country-specific calibration via genderize.io
Best use case
pipeworx-genderize is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Predict the likely gender associated with a first name — with optional country-specific calibration via genderize.io
Teams using pipeworx-genderize should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/pipeworx-genderize/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How pipeworx-genderize Compares
| Feature / Agent | pipeworx-genderize | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Predict the likely gender associated with a first name — with optional country-specific calibration via genderize.io
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Genderize
Predict the statistical gender distribution of a first name based on a database of millions of records. Optionally calibrate predictions by country, since names like "Andrea" skew differently in Italy vs. the US.
## Tools
- **`predict_gender`** — Gender prediction from a first name. Returns the predicted gender and probability (0-1).
- **`predict_gender_country`** — Same prediction with country-specific calibration using ISO 3166-1 alpha-2 codes.
## Use cases
- Personalizing marketing content based on likely gender of a first name
- Demographic analysis of customer databases
- Research on name-gender associations across cultures
- Form pre-filling where gender context helps UX
## Example
```bash
curl -s -X POST https://gateway.pipeworx.io/genderize/mcp \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"predict_gender_country","arguments":{"name":"Andrea","country_id":"IT"}}}'
```
```json
{
"name": "Andrea",
"gender": "male",
"probability": 0.98,
"count": 54032,
"country_id": "IT"
}
```
## Setup
```json
{
"mcpServers": {
"pipeworx-genderize": {
"command": "npx",
"args": ["-y", "mcp-remote@latest", "https://gateway.pipeworx.io/genderize/mcp"]
}
}
}
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