Extract and Freeze Key Terms Up Front
Technical documentation often hinges on a handful of domain-specific nouns. Before engaging the engine, identify terms that must remain unchanged—proprietary component names, industry-standard acronyms, or trademarked labels. Claude respects explicit instructions well, so provide a simple glossary in your prompt. This prevents inconsistency across long documents where the same term might otherwise drift between translations.
Preserve Formatting Tokens and Code Blocks
Markdown tables, code snippets, and API call examples can break if the model treats them as prose. Instruct the engine to leave these sections untouched or to translate only inline comments. Check a sample early: if a code fence loses its syntax or a table misaligns, adjust your prompt to fence off these elements before continuing with the full file.
Batch Long Documents in Logical Sections
Claude handles extended context, but chapter-length technical manuals can still test limits. Split at natural boundaries—chapters, appendices, or major procedure groups—rather than arbitrary character counts. This preserves cross-reference accuracy and keeps terminology consistent. After each batch, review the first and last paragraphs for coherence before moving on.
A Five-Minute Check Before You Commit
Run a 500-word sample through Claude within Immersive Translate, then compare it against your glossary and formatting requirements. If the output matches your standards, proceed. For broader context on model strengths across different content types, see our guide on choosing a model for Technical documentation. Best AI model for translating technical documentation