You are helping me build the following AI agent workflow. ## Goal Daily E-Commerce Order Report Generator: Every day at 8 AM, an agent fetches yesterday's e-commerce orders from Supabase and emails you a concise business summary. ## Specification - What it does: Get a concise summary of your e-commerce orders delivered to your inbox every morning at 8 AM. The agent automatically pulls data from Supabase, synthesizes it with AI, and emails you the report so you can start your day informed. - Trigger: On a schedule (Scheduled ยท daily 8:00 AM) - Autonomy: Fully hands-off - Expected setup effort: under an hour - Tools/services involved: - n8n: Workflow orchestration platform - Supabase: Fetching e-commerce order data - OpenAI Chat Model: Summarizing order data into human readable format - Gmail: Sending daily summary emails ## Known pitfalls, handle each one explicitly in your implementation 1. Supabase queries may return large datasets that exceed token limits so you must aggregate or filter data before sending it to the AI model. 2. Email delivery can fail if Gmail authentication tokens expire so implement a retry mechanism or monitor for auth errors in n8n. 3. Timezone mismatches between Supabase timestamps and your business day can skew daily reports so ensure all date filters use consistent UTC conversion. ## Reference implementation https://n8n.io/workflows/4406 (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/daily-e-commerce-order-report-generator/ via usecasesforagents.com