Weekly Sales Briefing Skill

Generates a structured Amazon sales briefing for {{seller_name}} from DataDoe production data, rendered as an interactive HTML card artifact.

Configuration (hardcoded)

• Seller: {{seller_name}}
• Seller ID: {{seller_id}}
• MCP base: https://mcp.datadoe.com/mcp/v1
• Currency: {{currency_code}} ({{currency_symbol}})
• "This week": Rolling last 7 days (today - 7 through yesterday, inclusive)
• "Last week": The 7 days before that (today - 14 through today - 8)
• "Last month": Same 7-day window from 4 weeks ago (today - 35 through today - 29) Use today's actual date from the system context to compute all date ranges at runtime.

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Data Source

Use Export source ID 401ffcd7e5 — "Sales & Traffic by ASIN & Date". Key columns to request: date, child_asin, product_name, total_sales, total_units, total_orders

You need three separate exports covering three date windows:

1. This week: [today-7, today-1] (7 days)
2. Last week: [today-14, today-8] (7 days)
3. Last month (same window): [today-35, today-29] (7 days)

   Tip: Fire all three exports concurrently, then poll them together. Each export typically completes in under 30 seconds. Poll every 5 seconds. Never give up before completion.

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Step-by-step Workflow

1. Compute date ranges

Calculate the three date windows using today's date. Format as YYYY-MM-DD.

2. Create three exports

Call exports_create three times (concurrently if possible) with:

• sellerOrVendorId: {{seller_id}}
• sourceId: {{export_source_id}}
• columns: ["date", "child_asin", "product_name", "total_sales", "total_units", "total_orders"]
• dateFrom / dateTo: the appropriate window per export

3. Poll until complete

Poll each export's status every 5 seconds. When all three are COMPLETED, download the raw CSV/JSON content.

4. Aggregate per ASIN

For each of the three windows, aggregate total_sales per child_asin + product_name. This gives you revenue per ASIN per period. Also compute total revenue across all ASINs for each window.

5. Compute KPIs

• This week revenue: sum of total_sales for this week
• vs last week: absolute {{currency_symbol}} change + % change
• vs last month (same window): absolute {{currency_symbol}} change + % change

6. Rank SKUs

• Top 5 by revenue this week: sort by this week's total_sales descending, take top 5. Show ASIN, product name (truncated to ~40 chars), revenue, units.
• Top 3 drops vs last week: compute this_week_revenue - last_week_revenue per ASIN. Sort ascending (most negative first), take top 3. Show ASIN, name, this week revenue, last week revenue, and {{currency_symbol}} / % drop. Only include ASINs that had revenue in both periods.

7. Generate 1–2 insights

Write short, sharp observations using the data. Examples:

• "Revenue down 8% WoW, driven by SKU X dropping £Y"
• "Top performer [SKU] up £Z vs last week"
• "3 SKUs declined >20% WoW — may indicate stock or ranking issues" Keep each insight to one sentence.

8. Render the HTML card artifact

Produce a single-file HTML artifact. See the Output Format section below.

Output Format

Render a polished, self-contained HTML card. Requirements:

• Dark/neutral palette — professional seller-dashboard aesthetic
• Four sections clearly delineated:
  1. KPI Block — three metric tiles: This Week Revenue / vs Last Week / vs Last Month. Use color coding: green for positive, red for negative, neutral for flat.
  2. Top 5 SKUs by Revenue — clean table or card list. Show rank, product name (truncated), ASIN, revenue ({{currency_symbol}}), units sold.
  3. Biggest Drops vs Last Week — top 3 ASINs with largest {{currency_symbol}} decline. Show name, this week {{currency_symbol}}, last week {{currency_symbol}}, Δ{{currency_symbol}}, Δ%.
  4. Insights — 1–2 bullet points in a highlighted panel.
• Header: "{{seller_name}} — Weekly Sales Briefing", subtitle showing the date range (e.g. "27 Apr – 3 May 2025")
• Footer: "Data via DataDoe · Generated [today's date]"
• No external dependencies (pure HTML/CSS/JS, inline everything)
• Responsive — readable at typical desktop artifact width

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Error Handling

• If an export fails, retry once. If it fails again, note the error in the artifact and show partial data.
• If a date range returns zero rows (e.g. data not yet available for very recent dates), shift the window back one day and note this in the artifact.
• If product_name is empty for an ASIN, display the ASIN itself as the label.
• Rate limit (HTTP 429): wait the Retry-After seconds, then retry.

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Adapting for Other Sellers (Universal Pattern)

This skill is hardcoded for {{seller_name}} but the pattern is universal. To adapt for another Amazon seller:

1. Replace the Seller ID with the target seller's ID (retrieve via sellers_and_vendors_list).
2. Update the currency symbol to match the {{marketplace}} (e.g. € for DE, $ for US).
3. Adjust the header branding.
4. The DataDoe export source ID (401ffcd7e5) and column names are universal across all sellers. The three-window rolling comparison approach (this week / last week / same window 4 weeks ago) works for any Amazon {{marketplace}} and any granularity.