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sla-compliance-monitor

当用户需要监控支持工单或服务请求的SLA合规性时,此技能通过查询数据库、分析PDF中的SLA文档以及生成自动化通知来识别过期项目。它处理1)数据库探索以查找相关表(如支持工单、用户),2)PDF分析以提取SLA规则和电子邮件模板,3)SQL查询以根据用户服务水平识别超出响应时间的工单,以及4)使用提取的模板为经理提醒和客户道歉自动生成电子邮件。触发条件包括'SLA合规性'、'过期工单'、'响应时间监控'、'发送提醒邮件'、'道歉邮件'、'工单监控' 和 '服务水平协议'。

person作者: jakexiaohubgithub

SLA Compliance Monitor

Overview

This skill automates the monitoring of Service Level Agreement (SLA) compliance for support tickets. It identifies tickets that have exceeded their first response time based on user service levels, extracts email templates from SLA documentation, and sends automated notifications to responsible managers and affected customers.

Prerequisites

Ensure the following tools are available:

  • Snowflake database access (for snowflake-* tools)
  • Filesystem access to locate SLA documentation PDFs
  • PDF processing tools (pdf-tools-*)
  • Email sending capability (emails-send_email)

Core Workflow

Phase 1: Environment Discovery

  1. Identify the target database:

    • List available databases using snowflake-list_databases
    • Look for databases with names suggesting SLA/ticket monitoring (e.g., SLA_MONITOR)
  2. Explore the filesystem for SLA documentation:

    • List allowed directories using filesystem-list_allowed_directories
    • Search for PDF files containing SLA information (e.g., sla_manual.pdf, slamanual.pdf)
    • Extract archived documents if needed (e.g., .tar.gz files)

Phase 2: Schema & Document Analysis

  1. Examine database structure:

    • List schemas in the target database
    • List tables, focusing on SUPPORT_TICKETS and USERS tables
    • Describe table structures to understand column relationships
  2. Analyze SLA documentation:

    • Read PDFs to extract SLA rules (response times per service level)
    • Extract email templates for manager reminders and customer apologies
    • Critical: Verify document validity - ignore documents marked as "OBSOLETE"

Phase 3: Identify Overdue Tickets

  1. Query for overdue tickets:

    • Join SUPPORT_TICKETS with USERS on USER_ID
    • Filter for tickets where FIRST_RESPONSE_AT IS NULL
    • Calculate hours elapsed since CREATED_AT
    • Apply SLA thresholds based on SERVICE_LEVEL:
      • basic: 72 hours
      • pro: 36 hours
      • max: 24 hours
    • Order results by service level priority (max → pro → basic) then creation date
  2. Use the SQL query template from references/sla_query.sql

Phase 4: Generate & Send Notifications

  1. Organize tickets by responsible manager using CUSTOMER_MANAGER field
  2. Send manager reminder emails:
    • Use template from assets/manager_reminder_template.txt
    • List tickets in max → pro → basic order
    • Include ticket numbers and service levels
  3. Send customer apology emails:
    • Use template from assets/customer_apology_template.txt
    • Customize with:
      • {TICKET_NUMBER}
      • {SECOND_REPLY_TIME} (based on service level: max=18h, pro=36h, basic=72h)

Key Considerations

  • Document Version Control: Always check for "OBSOLETE" markers in PDFs
  • Time Calculations: Use TIMESTAMPDIFF(HOUR, CREATED_AT, CURRENT_TIMESTAMP()) for accurate elapsed time
  • Email Templates: Strictly follow the templates specified in the SLA documentation
  • Error Handling: If no overdue tickets are found, provide a clear status message
  • Data Privacy: Ensure email addresses are handled appropriately

Output

Provide a summary report including:

  • Number of overdue tickets identified
  • Breakdown by service level and manager
  • Confirmation of emails sent
  • Any errors or warnings encountered