Support Response Time Context Note

WHAT IT DOES

AI-powered support response time context note that recommends appropriate response times for support tickets and customer inquiries. The script reads a support ticket or customer inquiry from the current page—ticket content, priority, customer tier, and issue type—and generates a recommendation for appropriate response time based on the context. The AI analyzes the ticket to suggest a response timeline (immediate/within hours/within day/within week), considering factors like urgency, customer importance, issue severity, and support team capacity. You can customize the report format (brief/detailed) and toggle inclusion of urgency analysis, customer tier, issue severity, team capacity, and SLA context. The user reviews the output before copying or using it.

WHERE IT RUNS

Works on all support ticket and customer inquiry pages (match pattern *://*/*), including help desk platforms, ticketing systems, customer service portals, and any page containing support tickets or customer inquiries.

HOW TO USE

Install the script and navigate to any support ticket or customer inquiry page. The Support Response Time Context Note appears in the panel. Configure your preferred report format and toggle inclusion of urgency analysis, customer tier, issue severity, team capacity, and SLA context using the settings controls. Click "Recommend" to analyze the current page. The AI extracts ticket content and generates a response time recommendation. Review the output in the panel. Click "Copy to Clipboard" to copy the recommendation for use in your support workflow. Adjust the settings and regenerate if you want a different level of detail.

REAL MECHANISM: DOM CONTENT EXTRACTION WITH AI RESPONSE TIME RECOMMENDATION AND REVIEW GATE

This script uses a hybrid extraction approach that prioritizes structured content when available. First, it checks for WebMCP (navigator.modelContext), a W3C proposal that exposes structured tools on the page. If available, it calls getContent() to obtain structured ticket data. If WebMCP is not present—the common case today—it falls back to DOM scraping using targeted selectors for ticket sections (ticket-content, ticket-details, support-ticket, issue-content, ticket-priority, customer-info, issue-type, case-details, and support-request). It also scans for ticket-related keywords (urgent, priority, critical, issue, problem, request, help, unable, error, bug, support) in paragraphs and headings. The extracted text is sent to an AI backend via GM_xmlhttpRequest, which processes it with a system prompt that includes the user's report format and inclusion preferences. The AI returns a response time recommendation (up to 150 words) with suggested timeline and reasoning. The response is displayed in a bordered container for review before copying. Copy-to-clipboard uses GM_setClipboard. All settings (reportFormat, includeUrgency, includeCustomerTier, includeIssueSeverity, includeTeamCapacity, includeSLA) are persisted via GM_setValue. The script enforces a review-before-use pattern: the user must read and approve the AI output before copying it.

THE PANEL

Drag the panel anywhere on screen by clicking and holding the header. It snaps to screen edges when released. Collapse it to a small bubble by clicking the minimize button, and expand it back by clicking the bubble. Resize the panel from any corner. Press Escape to close the configuration panel. Your position and size preferences are saved automatically per site.

PLEASE NOTE

This script requires the free BotGentz browser extension and an active AI subscription for the recommendation service. AI-generated recommendations should be reviewed for accuracy before use—the AI may misinterpret urgency or miss important context. The script reads the current page content and sends it to the AI backend for processing; no data is stored or logged. Websites change frequently; if the script stops detecting ticket content, check for updates to the extraction selectors.