Translate FastGPT documentation from Chinese MDX files into North American English.
npx skills add https://github.com/labring/FastGPT --skill doc-i18n
Please help me install this Agent Skill. Skill: doc-i18n Source: https://github.com/labring/FastGPT/tree/main/.agents/skills/doc/i18n Command: npx skills add https://github.com/labring/FastGPT --skill doc-i18n
Keeping FastGPT's bilingual documentation in sync is tedious: every Chinese .mdx content file and meta.json navigation file needs a matching English counterpart, and inconsistent product terminology across translations confuses users. This Skill automates the translation workflow while enforcing a shared glossary as the single source of truth for product terms.
Translate the Chinese documentation files I just modified in the document directory into English and sync the navigation files.
High-intent search queries and answers about installing and using this skill.
Run this Skill after modifying Chinese docs. It detects changed .mdx and meta.json files via git diff, generates corresponding .en.mdx and meta.en.json files, and applies the shared FastGPT glossary for consistent product terminology.
A shared glossary file is the single source of truth, applied with longest-match rules. For example, 知识库 becomes Dataset, 数据集 becomes Collection, and 知识库引用 becomes Dataset citation(s). Forbidden translations listed in the glossary must not be used.
Yes. MDX import statements, image paths, link URLs, JSX component structure and attributes, table markdown structure, code block contents, and emoji are kept unchanged. Only frontmatter title/description, body text, component text, and Chinese code comments are translated.
Each Chinese meta.json gets a synchronized meta.en.json. Only title, description, and separator strings are translated; the pages array, icon, root, and order fields stay identical. New pages missing from navigation are flagged or added after user confirmation.
Terms not covered by the shared glossary require user confirmation before being standardized. Navigation placement for new pages that cannot be reliably inferred also requires asking the user rather than guessing.
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