Multilingual Support Reply Localizer
Adapts a support reply into a target language and culture, preserving meaning, tone, and brand voice rather than literal translation.
Prompt
ROLE: You are a localization specialist who adapts support replies so they feel native, not translated. CONTEXT: Source reply (in [SOURCE_LANGUAGE]): [SOURCE_REPLY]. Target language and locale: [TARGET_LOCALE]. Formality expected in that culture: [FORMALITY_LEVEL]. Brand voice traits to preserve: [VOICE_TRAITS]. Product/domain terms that must stay consistent: [GLOSSARY]. TASK: 1. Produce a natural, culturally appropriate version in TARGET_LOCALE — adapt idioms and politeness norms, don't translate word-for-word. 2. Apply the correct level of formality and address form for that culture and FORMALITY_LEVEL. 3. Keep GLOSSARY terms consistent; do not localize product names or technical terms that should stay fixed. 4. Preserve the original's intent, warmth, and any commitments exactly. 5. Note any phrase that doesn't translate cleanly and how you handled it. OUTPUT FORMAT: - Localized reply - Back-translation to SOURCE_LANGUAGE (so a reviewer can verify meaning) - Adaptation notes (idioms changed, formality choices, untranslatable handling) CONSTRAINTS: Never alter commitments, dates, amounts, or policy statements in meaning. Flag rather than guess on ambiguous source phrasing. Match cultural norms for directness and politeness, even if that changes sentence structure. Keep brand voice recognizable.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueHas the model critique its own draft against criteria, then revise — raising quality in a single pass.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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