Is this just machine translation?

No. Translation swaps words; localization adapts assumptions. The adapter prompt rewrites currencies, units, date formats, idioms, holidays, names, and tone so the prompt feels native to the target culture rather than translated.

What does the cultural bias scan detect?

It flags US-centric defaults like dollar amounts, imperial units, MM/DD dates, "ZIP code", US-only holidays, and informal address such as "guys". These often slip through unnoticed and break a prompt in other markets.

Do I need an API key?

No. This tool builds an adapter prompt locally in your browser and runs the bias scan with no network calls. You then paste the prompt into whatever LLM you already use.

How many locales are supported?

Thirty-plus, spanning major European, Asian, Middle Eastern, and Latin American markets, each with its own currency, date, unit, and formality conventions baked into the adapter instructions.

Will it keep my prompt's intent?

Yes. The generated instructions explicitly tell the model to preserve the original purpose and only change locale-specific surface details, then explain each change so you can verify nothing important shifted.

Prompt Localization Adapter

Prompt localization adapter

A prompt that works perfectly for one market often breaks quietly in another. It quotes prices in dollars, uses miles and Fahrenheit, assumes a Monday-to-Friday US work week, or addresses everyone as “guys”. The prompt localization adapter takes your original prompt, scans it for these implicit cultural assumptions, and generates a ready-to-run adapter prompt that rewrites it for a target locale — preserving intent while making every surface detail feel native.

How it works

You paste your prompt and choose a source and target locale from a list of 30+ markets, each with its own currency, date format, measurement system, and formality norms. The tool runs a quick local scan for US-centric or culture-specific patterns — dollar signs, imperial units, US holidays, “ZIP code”, informal address — and flags each one. It then assembles an adapter prompt that instructs an LLM to localize (not merely translate) the original and to append a list of every change it made and every bias it removed. Everything runs in your browser; no key or network call is needed to build the prompt.

Tips and notes

Read the bias flags first. They often reveal an assumption you didn’t know you’d baked in — fix obvious ones by hand before localizing.
Localize tone, not just words. German and Japanese prompts may need a more formal register; Dutch tolerates directness that reads as rude elsewhere.
Watch currency and units in examples. A “$19.99” sample value should become the local currency and a realistic local price, not a direct conversion.
Verify the change list. The adapter prompt asks the model to explain every edit — skim it to confirm nothing load-bearing shifted.