Empathetic Support Response Refiner
Transform harsh or defensive support drafts into calm, empathetic, and de-escalating customer communications.
Customise & copy
Add the context you have. The prompt updates as you work.
Paste the harsh or defensive draft response that needs rewriting.
Describe the situation, customer emotions, and the core issue.
Select how deeply empathetic the response should sound.
Live prompt
3 fieldsRewrite the following customer support draft response to ensure a calm, empathetic tone that validates the customer's frustration, avoids defensiveness, and removes any hint of customer blame. Context of the customer's issue: Customer is extremely upset because their account was locked right before a major deadline. Original draft response: You typed your password incorrectly five times, which is why your account got locked out. You need to follow the reset instructions properly. Desired tone intensity: High Empathy & De-escalation Provide only the rewritten, ready-to-send response.
Proof before you use it
A real example
Tested on gemini-3.1-flash-lite on 2026-09-04
{
"original_draft": "We already shipped the hardware to the address you provided in the portal, so if it's missing you have to take it up with the courier service.",
"tone_intensity": "Standard Calm & Professional",
"customer_context": "An IT manager at a hospital is panicking because an urgent replacement server part hasn't arrived and tracking shows it was delivered to a loading dock."
}A small ritual that works
How to use it
- 01Paste your defensive or harsh draft into the 'Original Draft Response' field.
- 02Briefly describe the customer's situation and emotional state in the 'Customer Context' field.
- 03Select your preferred level of empathy and click generate.
- 04Review the output and send the refined, professional response to the customer.
Why it works
The prompt establishes clear constraints for transforming defensive customer support drafts into calm, empathetic communications. By defining specific structural inputs (customer context, original draft, and tone intensity) and testing them against real scenarios, the prompt effectively guides the language model to validate user frustration, strip away blame, and pivot toward constructive resolution.
Where it fails
Output A contains an unresolved placeholder ([Insert Link]) that requires a manual edit before sending, demonstrating that the prompt can occasionally leave technical insertion points unmanaged.
Customisation tips
Users can adjust the tone intensity dropdown options to match specific corporate communication guidelines, or add variable fields for company-specific policies and support channels.
Watch-outs
- Review generated outputs for generic placeholder text like '[Insert Link]' before sending to customers.
- Ensure the tone intensity selected aligns appropriately with the severity of the customer context.
Works in
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