Generate fake test data

When the user asks for fake data — names, addresses, companies, products, mock users, test data, or localized placeholder data — reach for FakerAPI. Generates realistic synthetic data in a single unauthenticated GET with locale support and deterministic seeds.

generate-fake-test-data · v1 · updated 2026-04-16

Agents: This page is a SKILL.md-style capability guide. For JSON, call GET /api/skills/generate-fake-test-data. To drop this into a local Claude Code install, copy the frontmatter + body below into ~/.claude/skills/generate-fake-test-data/SKILL.md.

When to use this skill

When the user asks for fake names, addresses, companies, products, or any mock data for testing, prototyping, or seeding a development database — FakerAPI generates realistic-looking synthetic data on demand with no auth. The locale parameter makes it one of the few free APIs that produces locale-appropriate names and formatting (German names look German, French addresses look French). For real geocoded addresses, this is the wrong skill (the coordinates are random, not real). For production identity verification, use a dedicated identity API instead.

Your best first call

curl "https://fakerapi.it/api/v2/persons?_quantity=3&_locale=de_DE"

No auth. No key. Returns a JSON envelope with status, code, locale, seed, total, and a data array of person objects. The _quantity parameter (1–1000) controls record count; _locale (e.g., en_US, de_DE, fr_FR, it_IT) localizes names, addresses, and phone formatting. Using de_DE here because German locale demonstrates that localization actually works — names like "Günther" and addresses with German formatting are noticeably different from the en_US default.

Key fields in each person object:

firstname, lastname — locale-appropriate names
email — a plausible-looking email (not a real mailbox)
phone — formatted for the locale
birthday — ISO date string
gender — "male" or "female"
address — nested object with street, city, zipcode, country, country_code, latitude, longitude
website, image — placeholder URLs

Fallbacks (when the best call isn't enough)

Custom field combinations (username + password + IBAN) → /custom?customfield1=userName&customfield2=password&customfield3=iban&_quantity=3 — use when you need specific field types that don't map to any standard endpoint. Available types include userName, freeEmail, companyEmail, password, iban, isbn, url, ip, macAddress, uuid, color, mimeType, and more.
Product data for e-commerce testing → /products?_quantity=3 — returns name, description, price, net_price, taxes, ean, upc, categories, tags.
Company data for B2B testing → /companies?_quantity=2 — returns name, email, vat, phone, country, a nested addresses array, and a contact person object.

Pitfalls

_quantity defaults to 10 and caps at 1000. Omitting it means you always get 10 records — use _quantity=1 for a single record or match your actual need.
The address object inside each person generates a random country paired with random latitude/longitude — the coordinates do NOT correspond to the listed country. They are independent random values.
The /images endpoint returns URLs from picsum.photos, an external placeholder service. Those URLs are not under FakerAPI's control and may change or rate-limit independently.
_seed produces deterministic output per endpoint, but different endpoints with the same seed produce different data — seed consistency is per-call, not session-wide.

One-line summary for the user

I can generate realistic fake data — names, addresses, companies, products — via FakerAPI with locale support and deterministic seeds, no auth required.

APIs this skill uses

Faker API · primary · verified

A collection of completely free APIs that help web developers and web designers generate fake data in a fast and easy way. No registration is required, no tokens, no authentication.

SKILL.md source (frontmatter + body)

---
name: generate-fake-test-data
description: When the user asks for fake data — names, addresses, companies, products, mock users, test data, or localized placeholder data — reach for FakerAPI. Generates realistic synthetic data in a single unauthenticated GET with locale support and deterministic seeds.
---

## When to use this skill

When the user asks for fake names, addresses, companies, products, or any mock data for testing, prototyping, or seeding a development database — FakerAPI generates realistic-looking synthetic data on demand with no auth. The locale parameter makes it one of the few free APIs that produces locale-appropriate names and formatting (German names look German, French addresses look French). For real geocoded addresses, this is the wrong skill (the coordinates are random, not real). For production identity verification, use a dedicated identity API instead.

## Your best first call

```bash
curl "https://fakerapi.it/api/v2/persons?_quantity=3&_locale=de_DE"
```

No auth. No key. Returns a JSON envelope with `status`, `code`, `locale`, `seed`, `total`, and a `data` array of person objects. The `_quantity` parameter (1–1000) controls record count; `_locale` (e.g., `en_US`, `de_DE`, `fr_FR`, `it_IT`) localizes names, addresses, and phone formatting. Using `de_DE` here because German locale demonstrates that localization actually works — names like "Günther" and addresses with German formatting are noticeably different from the `en_US` default.

Key fields in each person object:

- `firstname`, `lastname` — locale-appropriate names
- `email` — a plausible-looking email (not a real mailbox)
- `phone` — formatted for the locale
- `birthday` — ISO date string
- `gender` — `"male"` or `"female"`
- `address` — nested object with `street`, `city`, `zipcode`, `country`, `country_code`, `latitude`, `longitude`
- `website`, `image` — placeholder URLs

## Fallbacks (when the best call isn't enough)

- **Custom field combinations (username + password + IBAN)** → `/custom?customfield1=userName&customfield2=password&customfield3=iban&_quantity=3` — use when you need specific field types that don't map to any standard endpoint. Available types include `userName`, `freeEmail`, `companyEmail`, `password`, `iban`, `isbn`, `url`, `ip`, `macAddress`, `uuid`, `color`, `mimeType`, and more.
- **Product data for e-commerce testing** → `/products?_quantity=3` — returns `name`, `description`, `price`, `net_price`, `taxes`, `ean`, `upc`, `categories`, `tags`.
- **Company data for B2B testing** → `/companies?_quantity=2` — returns `name`, `email`, `vat`, `phone`, `country`, a nested `addresses` array, and a `contact` person object.

## Pitfalls

- `_quantity` defaults to 10 and caps at 1000. Omitting it means you always get 10 records — use `_quantity=1` for a single record or match your actual need.
- The `address` object inside each person generates a random `country` paired with random `latitude`/`longitude` — the coordinates do NOT correspond to the listed country. They are independent random values.
- The `/images` endpoint returns URLs from `picsum.photos`, an external placeholder service. Those URLs are not under FakerAPI's control and may change or rate-limit independently.
- `_seed` produces deterministic output per endpoint, but different endpoints with the same seed produce different data — seed consistency is per-call, not session-wide.

## One-line summary for the user

I can generate realistic fake data — names, addresses, companies, products — via FakerAPI with locale support and deterministic seeds, no auth required.

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