Localization files usually have keys and values, but often lack context for proper translation. Ideally, each key should have a comment explaining its use, but this is rarely done. This lack of context leads to poor localization, as short UI texts can be hard to translate accurately.

Crowdin offers tools to add context, but doing this for large projects can be tedious and time-consuming. This experiment with the Crowdin app aims to simplify the process by using code to explain text usage. The app pulls keys from your Crowdin project, analyzes your code to determine how each key is used, and saves this context back to Crowdin for better translations.

This open-source NPM package ensures security and can be run locally. When using OpenAI, your code remains secure. You can verify the extracted context before uploading it to Crowdin.

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