Tokenize UI text and generate translation dictionaries for static sites.
npx skills add https://github.com/Onlyaguest/ViviStableSkills --skill i18n-kit
Please help me install this Agent Skill. Skill: i18n-kit Source: https://github.com/Onlyaguest/ViviStableSkills/tree/main/i18n-kit Command: npx skills add https://github.com/Onlyaguest/ViviStableSkills --skill i18n-kit
Static sites and lightweight reports often require bilingual content delivered without relying on external APIs. i18n-kit provides an offline flow to tokenize UI text, generate language dictionaries, and embed a local language switcher for fully offline delivery.
Run a dry-run extract to collect texts and generate the i18n dictionary for your project.
High-intent search queries and answers about installing and using this skill.
To translate static HTML offline, you can tokenize UI text into stable keys and generate language dictionaries. This process enables fully offline bilingual output and local language switching without relying on external translation services.
Adding multilingual support to lightweight web projects involves a token-based workflow that extracts UI text into dictionary files. This approach produces language-specific static site builds with an optional offline language switcher, minimizing runtime dependencies.
Yes, you need Python to build offline translation dictionaries for static sites. The workflow requires Python and minimal runtime dependencies to tokenize text, generate dictionaries, and apply translations for your lightweight reports.
You tokenize UI text to generate an i18n dictionary by running a dry-run extract process. This collects texts from your static project and creates dictionary files mapping stable keys to multiple languages for offline delivery.
Yes, you can switch languages offline in a static report by applying translations to produce language-specific directories. An optional offline language switcher can be embedded to enable local language switching without external APIs.
You should avoid external translation services for bilingual static sites when delivering lightweight reports that must function fully offline. Using a local token-based dictionary workflow reduces external dependencies and ensures reliable offline delivery.
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