Restock Priority Alert

The SKUs about to stock out, ranked by urgency, with how many units to ship and by when - straight from DataDoe's FBA Inventory Health (Amazon's own restock recommendations, plus a velocity fallback). Stops the silent revenue loss of a hero SKU going to zero.

When to use this

• Weekly (or daily) restock planning.
• Before a promo or peak season.
• "What's about to run out / what do I need to ship."
• Trigger phrases: "restock", "what's about to stock out", "days of supply", "reorder", "low inventory", "how much to ship in", "stockout risk".

The framework. Rank by time-to-zero, not by units

1. Out now - available = 0 with recent velocity (units_shipped_t30 > 0) and little/no inbound. Losing sales right now. Top priority.
2. Imminent - days_of_supply below your lead time (default 30d) and not enough inbound to cover.
3. Covered - enough on-hand + inbound. Skip. Order by fewest days of supply. Attach Amazon's recommended_ship_in_quantity + recommended_ship_in_date.

Configuration

• MCP base: https://mcp.datadoe.com/mcp/v1
• Data source: FBA Inventory Health (amazon_fba_inventory_health). Daily snapshot - use the latest date. Not available in MX.
• Lead time / target cover: ask the user (default 30 days).

Step-by-step workflow (MCP-native)

1. sellers_and_vendors_list -> pick the seller.
2. exports_sources_get (query "inventory health") -> confirm amazon_fba_inventory_health enabled.
3. exports_create for amazon_fba_inventory_health, latest snapshot (from/to = last ~2 days), columns: sku, product_name, available, inbound_quantity, days_of_supply, units_shipped_t30, units_shipped_t7, recommended_ship_in_quantity, recommended_ship_in_date, fba_inventory_level_health_status. Order by days_of_supply ASC. Pull ~500.
4. Poll, download, keep the latest date per SKU.
5. Handle nulls (real data quirk): slow/near-zero SKUs often have days_of_supply = null. Fallback: daily velocity = units_shipped_t30 / 30; days left = available / velocity (skip SKUs with no velocity - they are dead stock, not restock). Prefer Amazon's recommended_ship_in_quantity when present.
6. Bucket (out-now / imminent / covered) and render, most urgent first.

Output format

1Restock Priority - {marketplace} - {date}   (lead time {L}d)
2
3OUT NOW (losing sales)
4SKU                     avail  t30   inbound  ship-in   by
5{sku}                   0      {n}    {n}      {qty}     {date}
6
7IMMINENT (< {L} days)
8SKU                     avail  DoS   t30   inbound  ship-in  by
9{sku}                   {n}    {d}   {n}   {n}      {qty}    {date}
10
11Covered: {count} SKUs OK. Dead stock (no sales): {count} - not restocked.
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Worked example (illustrative)

SKU A: available 1, sold ~24 in the last 30d (~0.8/day), only 18 inbound, days of supply ~0. Amazon recommends shipping in ~86 units by a date this week -> OUT-NOW priority; ship the recommended quantity. SKU B: available 0, sells ~65/mo, but ~418 already inbound -> covered soon, lower priority despite being at zero (inbound covers it). That inbound-aware ranking is the point: at-zero alone isn't the trigger; at-zero without enough inbound is.

Quality self-check

• Did I use the latest snapshot date only?
• Did I subtract inbound before crying "stockout"?
• Did I fall back to t30 velocity when days_of_supply is null, and skip no-velocity dead stock (don't tell them to restock a non-seller)?
• Did I surface Amazon's ship-in qty/date rather than guessing?

Common mistakes

• Flagging at-zero SKUs that already have plenty inbound.
• Recommending restock for dead stock (0 sales) - that's a removal decision, not restock.
• Ignoring null days_of_supply instead of computing from velocity.
• Using a stale snapshot (multiple dates) - collapse to MAX(date).

Notes

• Read-only.
• Pairs with a removal / excess-inventory skill for the opposite problem (overstock).
• A DataDoe skill, built on the DataDoe FBA Inventory Health source (uses Amazon's native restock recommendations where available).