집
GitHub 커밋 기록 자동 요약 생성
AI
37
37
소프트웨어 프로젝트의 GitHub 커밋 기록에서 명확하고 간결한 변경 요약을 생성하고 버전 업데이트 핵심 변경 내용을 정리해 개발 팀의 프로젝트 진행 상황 동기화를 돕습니다.
프롬프트 내용
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Sort through all commit records from the past two weeks of a specified GitHub repository, organize all changes into three categories: new features, bug fixes and architecture adjustments, and write an easy-to-understand natural language summary for the project team's weekly meeting, avoid jargon and keep the language straightforward.
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지정된 GitHub 저장소의 최근 2주간 모든 커밋 기록을 정리하고 기능 추가, 버그 수정, 아키텍처 조정 세 가지 카테고리로 모든 변경점을 분류한 뒤, 프로젝트 팀 주간 회의 공유용으로 이해하기 쉬운 자연어 요약을 작성하세요. 전문 용어를 피하고 간결한 언어로 유지하세요.
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이커머스 티켓 분류기
Analyze the following customer service message from an e-commerce platform and determine its business category. The possible categories are: Logistics Inquiry, Return/Exchange Request, Product Quality Issue, Price Dispute, or Other Inquiry. Output only the category name without any explanation or additional text. If the message cannot be clearly classified, output 'Other Inquiry'.
EC 티켓 분류
Act as a data analysis assistant for an e-commerce customer service system. Read the current list of pending customer inquiry tickets, automatically categorize them into four major categories based on the nature of the issue: logistics inquiry, product quality, return/exchange application, or complaint/suggestion. Extract key entities such as order numbers, product SKUs, and user sentiment tendencies, and finally output structured classification results for subsequent manual review or automatic routing.
EC 티켓 분류기
Act as an intelligent customer service assistant for an e-commerce platform. Receive the raw text of a user's inquiry, analyze its core intent and urgency, and categorize it into one of four types: pre-sales consultation, after-sales rights protection, logistics inquiry, or complaint/suggestion. Extract key entities such as order numbers, product names, and problem descriptions. Finally, output a structured classification result and handling suggestions, ensuring the response is accurate and complies with corporate customer service standards.
이커머스 티켓 분류기
Please analyze the following e-commerce customer service ticket content and classify it into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other Inquiry' based on predefined business rules. If the ticket involves multiple issues, prioritize the most urgent or core issue category. Ensure the classification result is accurate and aligns with actual business scenarios to enable the customer service team to respond quickly.
이커머스 티켓 분류
Please analyze the following e-commerce customer inquiry ticket content, automatically classify it into one of four categories: 'Logistics Inquiry', 'Return/Exchange Request', 'Product Quality Complaint', or 'Other Inquiry' based on business semantics, and briefly explain the classification basis to enable the customer service team to respond and handle it quickly.
전자상거래 고객 지원 티켓 분류
Analyze the provided customer inquiry text and categorize it into one of four predefined classes: pre-sales consultation, after-sales service, logistics inquiry, or complaint/suggestion based on business semantics. If an order number is mentioned, extract it; if emotional expression is present, label the sentiment as positive, neutral, or negative. The output must include the classification result, key entity extraction, and sentiment label, ensuring the logic aligns with standard e-commerce customer service protocols without additional explanatory reasoning.
