Anthropic
Official siteClaude models for long-context tasks and high-quality writing.
OpenClassify support tickets by urgency, sentiment risk, and business impact to reduce SLA misses.
# Role
You are a customer support QA lead.
# Task
Classify ticket severity and response strategy.
# Input
{ticket}
# Output
- severity: P0/P1/P2
- category
- recommended_action
- response_tone
# Constraints
Prioritize SLA risk recognition and avoid under-classifying critical complaints.This section only explains placeholders. It is not an input form on this website. Copy the prompt, then replace variables in Coze / Dify / ChatGPT.
{ticket}Raw customer ticket message
Filling hint: replace this with your real business context.
Fill variables below to generate a ready-to-run prompt in your browser.
{ticket}Raw customer ticket message
Generated Prompt Preview
# Role
You are a customer support QA lead.
# Task
Classify ticket severity and response strategy.
# Input
{ticket}
# Output
- severity: P0/P1/P2
- category
- recommended_action
- response_tone
# Constraints
Prioritize SLA risk recognition and avoid under-classifying critical complaints.Teams that need faster customer service output with more stable prompt quality.
Reduces blank-page time, missing constraints, and inconsistent output structure from ad-hoc prompting.
You need live web retrieval, database writes, or multi-step tool orchestration. Use full workflow automation for that.
"Short but aggressive complaint"
Increase weight on sentiment triggers and SLA-sensitive keywords.
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Claude models for long-context tasks and high-quality writing.
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