| name | shopify-admin-demand-forecast-reorder |
| role | merchandising |
| description | Read-only: forecasts demand per SKU using sales velocity and seasonality, then calculates reorder points and suggested purchase order quantities. |
| toolkit | shopify-admin, shopify-admin-execution |
| api_version | 2025-01 |
| graphql_operations | ["orders:query","productVariants:query","inventoryItems:query","inventoryLevels:query"] |
| status | stable |
| compatibility | Claude Code, Cursor, Codex, Gemini CLI |
Purpose
Forecasts future demand for each SKU based on historical sales velocity, trend analysis, and optional seasonality adjustments. Calculates reorder points (when to order) and suggested reorder quantities (how much to order) factoring in vendor lead times and safety stock. Read-only — no mutations.
Prerequisites
- Authenticated Shopify CLI session:
shopify store auth --store <domain> --scopes read_orders,read_products,read_inventory
- API scopes:
read_orders, read_products, read_inventory
Parameters
| Parameter | Type | Required | Default | Description |
|---|
| store | string | yes | — | Store domain |
| days_back | integer | no | 90 | Historical sales window for velocity calculation |
| forecast_days | integer | no | 30 | Days into the future to forecast demand |
| lead_time_days | integer | no | 14 | Default vendor lead time in days |
| safety_stock_days | integer | no | 7 | Extra days of safety stock buffer |
| vendor_filter | string | no | — | Scope to specific vendor |
| only_low_stock | boolean | no | false | Only show items projected to stock out within forecast window |
| format | string | no | human | Output format: human or json |
Safety
ℹ️ Read-only skill — no mutations are executed. Safe to run at any time.
Workflow Steps
-
OPERATION: orders — query
Inputs: query: "created_at:>='<NOW - days_back days>'", first: 250, select createdAt, lineItems { variant { id }, quantity }, pagination cursor
Expected output: All orders with line items for sales velocity calculation
-
Calculate per-variant sales velocity:
- Daily sales rate = total units sold / days_back
- Weekly trend: compare last 30 days vs prior 30 days for trend direction
- Forecasted demand = daily_rate × forecast_days × trend_multiplier
-
OPERATION: productVariants — query
Inputs: All variant IDs with sales history, first: 250, pagination cursor
Expected output: Variant details (SKU, title, product title, vendor)
-
OPERATION: inventoryLevels — query
Inputs: Inventory item IDs for stocked variants
Expected output: Current available quantities per location
-
Calculate reorder metrics:
- Days of Stock = current_inventory / daily_sales_rate
- Reorder Point = (lead_time_days + safety_stock_days) × daily_sales_rate
- Reorder Quantity = forecast_days × daily_sales_rate + safety_stock - current_inventory
- Stockout Date = today + (current_inventory / daily_sales_rate) days
- Order-By Date = stockout_date - lead_time_days
-
Sort by urgency: items closest to stockout first
GraphQL Operations
query SalesHistory($query: String!, $after: String) {
orders(first: 250, after: $after, query: $query) {
edges {
node {
createdAt
lineItems(first: 50) {
edges {
node {
quantity
variant { id }
}
}
}
}
}
pageInfo { hasNextPage endCursor }
}
}
query VariantInfo($ids: [ID!]!) {
nodes(ids: $ids) {
... on ProductVariant {
id
sku
title
product { id title vendor }
inventoryQuantity
inventoryItem { id }
}
}
}
query InventoryItemDetails($ids: [ID!]!) {
nodes(ids: $ids) {
... on InventoryItem {
id
unitCost { amount currencyCode }
tracked
inventoryLevels(first: 10) {
edges {
node {
quantities(names: ["available"]) {
name
quantity
}
location { id name }
}
}
}
}
}
}
query LocationInventory($locationId: ID!, $after: String) {
location(id: $locationId) {
inventoryLevels(first: 250, after: $after) {
edges {
node {
quantities(names: ["available"]) { name quantity }
item { id variant { id sku product { title } } }
}
}
pageInfo { hasNextPage endCursor }
}
}
}
Session Tracking
Claude MUST emit the following output at each stage. This is mandatory.
On start, emit:
╔══════════════════════════════════════════════╗
║ SKILL: Demand Forecast & Reorder Planner ║
║ Store: <store domain> ║
║ Started: <YYYY-MM-DD HH:MM UTC> ║
╚══════════════════════════════════════════════╝
After each step, emit:
[N/TOTAL] <QUERY|MUTATION> <OperationName>
→ Params: <brief summary of key inputs>
→ Result: <count or outcome>
On completion, emit:
For format: human (default):
══════════════════════════════════════════════
DEMAND FORECAST & REORDER PLAN (<days_back>d history → <forecast_days>d forecast)
SKUs analyzed: <n>
Avg daily velocity: <n> units/day
─────────────────────────────
⚠️ URGENT (stockout <7 days):
"<product>" SKU:<sku> Stock:<n> Days left:<n> ORDER BY: <date>
Reorder qty: <n> units Est. cost: $<n>
⏰ PLAN AHEAD (stockout 7-30 days):
"<product>" SKU:<sku> Stock:<n> Days left:<n> ORDER BY: <date>
✅ HEALTHY (>30 days stock):
<n> SKUs with adequate stock
Output: reorder_plan_<date>.csv
══════════════════════════════════════════════
For format: json, emit:
{
"skill": "demand-forecast-reorder",
"store": "<domain>",
"history_days": 90,
"forecast_days": 30,
"lead_time_days": 14,
"skus_analyzed": 0,
"urgent_reorders": [],
"planned_reorders": [],
"healthy_skus": 0,
"output_file": "reorder_plan_<date>.csv"
}
Output Format
CSV file reorder_plan_<YYYY-MM-DD>.csv with columns:
variant_id, sku, product_title, vendor, current_stock, daily_velocity, trend, days_of_stock, stockout_date, reorder_point, reorder_qty, order_by_date, est_cost
Error Handling
| Error | Cause | Recovery |
|---|
THROTTLED | API rate limit exceeded | Wait 2 seconds, retry up to 3 times |
| Zero sales velocity | Product never sold in window | Skip from reorder calc — flag as "no demand data" |
| No inventory tracking | Variant not tracked | Skip — cannot forecast untracked items |
Best Practices
- Set
lead_time_days per vendor if possible; default 14 is conservative.
- Use
safety_stock_days: 14 for high-value or slow-ship items.
- Run weekly and pipe output into a purchase order workflow.
- Cross-reference with
stock-velocity-report for velocity validation.
- Use with
dead-stock-identifier to avoid reordering items that aren't selling.
- For seasonal products, use a longer
days_back (180-365) to capture seasonal patterns.