Context-aware translation that preserves tone, style, and natural word order. Use when translating UI strings, documentation, marketing copy, or any multilingual content. Infers register, domain, and style from the source text and surrounding codebase context.
Scan existing locale files before translating to align with project conventions
Preserve placeholders and interpolation syntax
Translate meaning, not words
相關技能
Preserve emotional connotations — translate the feeling, not just the dictionary meaning (e.g., "alarming" carries urgency/concern, not merely "surprising")
Match register consistently throughout a single piece
Split, merge, or restructure sentences for target language naturalness
Flag ambiguous source text rather than guessing
Preserve domain terminology — if a term has established meaning in the field (e.g., harness, scaffold, shim, polyfill, middleware), keep it even if a "simpler" native word exists
Never produce literal word-for-word translations
Never mix registers within a single piece (formal + casual)
Never replace domain-specific terms with generic equivalents (e.g., "harness" → "framework", "shim" → "wrapper")
Never translate proper nouns unless existing translations do so
Never change the meaning to "sound better"
Never skip verification stage for batches > 10 strings
Never modify source file structure (keys, nesting, comments)
Never preserve source-language formatting artifacts that are unnatural in the target language. For CJK targets (Korean, Japanese, Chinese), em dashes (—), title case in headings, and trailing "-ing" participle clauses must be restructured — even when the source uses them. See resources/anti-ai-patterns.md rules 13–16.
Context Inference
No config file required. Instead, infer translation context from:
Existing translations in the project — scan sibling locale files to match register, terminology, and style already in use
File location — messages/, locales/, .arb files reveal the framework and format
Surrounding code — component names, comments, and variable names hint at domain and audience
Source text itself — register, formality, sentence structure reveal intent
If context is insufficient to make a confident decision, ask the user. Prefer one targeted question over a batch of questions.
Domain terms: Words that need consistent translation (check existing translations first)
Cultural references: Idioms, metaphors, humor that won't transfer directly
Sentence rhythm: Short/punchy vs. long/flowing — note parallel structures, intentional repetition, and emphasis patterns
Comprehension challenges: Terms or references target readers may struggle with — domain jargon lacking standard translations, cultural references (pop culture, history, social norms), implicit knowledge the author assumes, wordplay or puns, named concepts (e.g., "Dunning-Kruger effect"). For each, note: the original term, why it may confuse, and a concise plain-language explanation for a potential translator's note
Figurative language mapping: For each metaphor, simile, idiom, or figurative expression, classify the handling approach:
Interpret: Discard source image entirely, express the intended meaning directly in natural target language
Substitute: Replace with a target-language idiom or image that conveys the same idea and emotional effect
Retain: Keep the original image if it works equally well in the target language
Emotional connotations: Words carrying subjective feeling beyond dictionary meaning (e.g., "alarming" = urgency, "haunting" = lingering unease) — note the emotional effect to preserve in translation
Stage 2: Extract Meaning
Strip away source language structure. Ask yourself:
What is the author actually trying to say?
What emotion or tone should the reader feel?
What action should the reader take?
Do NOT start forming target sentences yet.
Stage 3: Reconstruct in Target Language
Rebuild from meaning, following target language norms:
Word order: Follow target language's natural structure.
EN → KO: SVO → SOV, move verb to end, particles replace prepositions
EN → JA: Similar SOV restructuring, honorific system alignment
EN → ZH: Maintain SVO but restructure modifiers (pre-nominal in ZH)
Register matching:
Infer from existing translations in the project, or from source text tone
English compound sentences often split into shorter Korean/Japanese sentences
English bullet points may merge into flowing paragraphs in some languages
Omission of the obvious:
Many languages (Korean, Japanese, Chinese, etc.) allow subject or pronoun omission when contextually clear
Don't force subjects or pronouns that feel unnatural in the target language
Stage 4: Verification Gate (blocking — do not emit output until every item is confirmed)
This stage is mandatory. Skipping any item is a bug, not a shortcut. Before producing the final translation, run the mechanical checks first, then the rubric.
A. Mechanical checks (run before rubric, must all pass):
CJK em dash scan: For Korean, Japanese, or Chinese targets, search the draft output for —. Every occurrence must be replaced with a comma, colon, parenthesis, or restructured sentence. Zero em dashes in the emitted output.
Placeholder integrity: Every {name}, {{count}}, %s, <tag>, and `code` from the source appears unchanged in the target.
Structure parity: Headings, list bullets, table rows, code blocks, and links match the source count and nesting.
Register consistency: One sentence-ending style throughout (don't mix -ㅂ니다 with -다, formal with casual).
If any mechanical check fails, revise and re-run. Do not proceed to the rubric until all pass.
B. Translation rubric (see resources/translation-rubric.md):
Does it read like it was originally written in the target language?
Are domain terms consistent with existing translations in the project?
Is the register consistent throughout?
Is the meaning preserved (not just words)?
Are cultural references adapted appropriately?
Are emotional connotations preserved (not flattened into neutral descriptions)?
C. Anti-AI patterns (see resources/anti-ai-patterns.md):
7. No AI vocabulary clustering or inflated significance
8. No promotional tone upgrade beyond the source
9. No synonym cycling — consistent terminology
10. No source-language word order leaking through
11. No unnecessary bold or formatting artifacts (em dashes already covered in mechanical check A)
12. No Europeanized patterns (unnecessary connectives, passive voice, noun pile-up, over-nominalization, forced pronouns, cleft calques)
D. Figurative language handling:
13. Were all metaphors/idioms handled per the classify decision (interpret/substitute/retain)?
14. Do figurative expressions read naturally in the target language, not as literal calques?
Translator's Notes Guidelines
When adding explanatory notes for terms, cultural references, or concepts that target readers may struggle with:
Format: 번역어（원어, 쉬운 설명） or 번역어(원어) for well-known terms that just need the original
Calibration by audience:
Technical readers: Skip annotation on common tech terms (API, deploy, refactor). Only annotate domain-specific or coined terms
General readers: More generous annotation. Explain jargon, cultural references, and domain concepts in plain language
Short texts (< 5 sentences): Minimize — only annotate terms the target audience is unlikely to know
Rules:
Annotate on first occurrence only — don't repeat the note
Keep notes concise (aim for under 10 words)
Explain what it means, not just provide the English original
Don't annotate self-explanatory terms or widely recognized loanwords
If a comprehension challenge was identified in Stage 1, use the pre-planned explanation
Refined Mode (Long-form Content)
For publication-quality translation of long-form content (articles, documentation, essays), extend the standard 4-stage workflow with three additional passes. Use when explicitly requested or when the content demands high polish.
When to use
User explicitly requests "refined", "publication quality", or "정밀 번역"
Important documents, official publications, marketing materials
Content where naturalness and readability are critical
Extended workflow
After completing Stage 1–4, continue with:
Stage 5: Critical Review
Re-read the translation against the source with fresh eyes. Produce a diagnostic review (no rewriting yet):
Accuracy: Compare paragraph by paragraph — any facts, numbers, or qualifiers altered?
Europeanized language: Scan for unnecessary connectives, passive voice, noun pile-up, over-nominalization, forced pronouns (see resources/anti-ai-patterns.md)
Figurative language fidelity: Cross-check metaphor mapping from Stage 1 — were all handled per the classify decision? Any literal calques that sound unnatural?
Emotional fidelity: Were subjective/emotional word choices flattened into neutral descriptions?
Tone drift: Does the register stay consistent from start to finish, or does it shift mid-document (e.g., formal intro drifting into casual explanation)?
Expression & flow: Flag sentences that still read like "translation-ese" — stiff phrasing, unnatural word order, awkward transitions
Translator's notes quality: Too many? Too few? Accurate and concise?
Stage 6: Revision
Apply all findings from Stage 5 to produce a revised translation:
Fix accuracy issues
Rewrite Europeanized expressions into native patterns
Re-interpret literally translated metaphors per the mapping
Restore flattened emotional connotations
Restructure stiff sentences for fluency
Adjust translator's notes per review recommendations
Stage 7: Polish
Final pass for publication quality:
Read as a standalone piece — does it flow as native content?
Smooth remaining rough transitions between paragraphs
Ensure narrative voice is consistent throughout
Final scan for surviving literal metaphors or translation-ese
Propose a translation, confirm with user before applying
Register conflict in source
Follow project's existing register, note the inconsistency
Placeholder in middle of sentence
Restructure around it; never break placeholder syntax
Translation too long for UI
Provide a shorter alternative with note
Multiple valid translations for a term
Pick the one most consistent with project's existing translations; note alternatives
Target language requires gendered forms
Follow source text intent; prefer gender-neutral forms when available in target language
Tone shifts across a long document
Re-read end-to-end after translating; normalize register to the dominant tone
How to Execute
Follow the translation method (Stage 1-4) step by step.
Before submitting, verify against resources/translation-rubric.md and resources/anti-ai-patterns.md.
Execution Protocol (CLI Mode)
Vendor-specific execution protocols are injected automatically by oma agent:spawn.
Source files live under ../_shared/runtime/execution-protocols/{vendor}.md.