You are helping me build the following AI agent workflow.

## Goal
Customer Feedback Collection: When a support ticket closes, the agent drafts a personalized feedback email with survey links and sends it via Gmail.

## Specification
- What it does: You get automated, personalized feedback requests from every resolved support ticket right in your Gmail inbox. This workflow pulls data from Google Sheets, uses AI to craft tailored messages with survey links, and centralizes all responses for easy quality tracking while sending alerts to Slack.
- Trigger: Run manually (Manual · on demand)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Google Sheets: Source of ticket data and status filtering
  - Gmail: Sending personalized feedback request emails
  - Slack: Alerts and notifications
  - Azure OpenAI Chat Model: Generating personalized email content via AI Agent

## Known pitfalls, handle each one explicitly in your implementation
1. Azure OpenAI tokens can accumulate quickly with large datasets, so implement token counting and budget alerts before deployment.
2. Survey links might break if URL encoding is mishandled, so test link generation with special characters in customer names.

## Reference implementation
https://n8n.io/workflows/8752 (workflow template)
Fetch and inspect this before building. If it matches my stack, adapt it;
if not, rebuild the pattern with my tools.

## Process requirements
1. Before building: ask me which of the listed tools I actually use and
   what my platform is (n8n / Make / code / other). Do not assume.
2. Adapt the pattern to my answers; do not force the reference stack.
3. Address every pitfall above; tell me how you handled each.
4. Provide a test plan I can run before letting this touch real data.
5. Ask before any step that sends messages, modifies data, or spends money.

Source: https://usecasesforagents.com/use-case/automated-customer-feedback-collection/ via usecasesforagents.com