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shopify-admin-return-cost-attribution

Included with Lifetime
$97 forever

Read-only: calculates the true cost of returns by reason and product — refund dollars, restocking impact, shipping cost lost, and COGS impact for items written off.

General

What this skill does


## Purpose
Quantifies the full cost of returns over a window — not just the refunded amount. Combines refund totals, lost shipping revenue, COGS for non-restockable items (e.g., `DEFECTIVE`), and restocking labor into a per-reason and per-product return P&L. Read-only. Use to prioritize which reasons or product lines deserve operational fixes — better packaging, size guides, listing accuracy.

## Prerequisites
- `shopify store auth --store <domain> --scopes read_orders,read_returns,read_inventory`
- API scopes: `read_orders`, `read_returns`, `read_inventory`

## Parameters

| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| store | string | yes | — | Store domain (e.g., mystore.myshopify.com) |
| format | string | no | human | Output format: `human` or `json` |
| days_back | integer | no | 90 | Lookback window for returns |
| group_by | string | no | reason | Aggregation level: `reason`, `product`, `sku`, or `reason_x_product` |
| min_returns | integer | no | 3 | Minimum returns per group to include in summary |
| writeoff_reasons | array | no | `["DEFECTIVE"]` | Return reasons whose items are treated as non-restockable (full COGS write-off) |
| flat_restocking_cost | float | no | 5.00 | Average labor cost per return line item to model restocking workload |

## Safety

> ℹ️ Read-only skill — no mutations are executed. Cost figures are estimates derived from `unitCost`, refund totals, and `flat_restocking_cost` — calibrate the flat-cost figure to your operation before treating outputs as accounting truth.

## Workflow Steps

1. **OPERATION:** `returns` — query
   **Inputs:** `query: "created_at:>='<NOW - days_back days>'"`, `first: 250`, select returns with line item pricing, product/variant, `inventoryItem.id`
   **Expected output:** All returns in window with per-line-item pricing

2. **OPERATION:** `orders` — query
   **Inputs:** For each return's `order.id`, fetch `refunds { totalRefundedSet refundLineItems { quantity subtotalSet totalTaxSet lineItem { id } } }`
   **Expected output:** Refund amounts mappable to line items

3. **OPERATION:** `inventoryItems` — query — batch unique `inventoryItem.id` from step 1; returns `unitCost` per item

4. Per line item compute: `refund_amount` (matched refundLineItem proportional to returned qty), `shipping_loss` (order shipping × line-item value share for full-order returns; else 0), `cogs_writeoff` (`unitCost × qty` only if `returnReason in writeoff_reasons`), `restocking_labor` (`flat_restocking_cost × qty`). Sum and aggregate by `group_by`.

## GraphQL Operations

```graphql
# returns:query — validated against api_version 2025-01
query ReturnsForCostAttribution($query: String!, $after: String) {
  returns(first: 250, after: $after, query: $query) {
    edges {
      node {
        id
        status
        createdAt
        totalQuantity
        order {
          id
          name
          totalShippingPriceSet { shopMoney { amount currencyCode } }
          totalPriceSet { shopMoney { amount currencyCode } }
        }
        returnLineItems(first: 50) {
          edges { node {
            id
            quantity
            returnReason
            fulfillmentLineItem { lineItem {
              id
              title
              quantity
              discountedTotalSet { shopMoney { amount currencyCode } }
              originalUnitPriceSet { shopMoney { amount currencyCode } }
              variant { id sku inventoryItem { id } }
              product { id title vendor }
            } }
          } }
        }
      }
    }
    pageInfo { hasNextPage endCursor }
  }
}
```

```graphql
# orders:query — validated against api_version 2025-01
query OrderRefundsForReturns($query: String!, $after: String) {
  orders(first: 250, after: $after, query: $query) {
    edges {
      node {
        id
        name
        refunds {
          id
          createdAt
          totalRefundedSet { shopMoney { amount currencyCode } }
          refundLineItems(first: 50) {
            edges { node {
              quantity
              subtotalSet { shopMoney { amount currencyCode } }
              totalTaxSet { shopMoney { amount currencyCode } }
              lineItem { id }
            } }
          }
        }
      }
    }
    pageInfo { hasNextPage endCursor }
  }
}
```

```graphql
# inventoryItems:query — validated against api_version 2025-01
query InventoryUnitCosts($ids: [ID!]!) {
  nodes(ids: $ids) {
    ... on InventoryItem {
      id
      unitCost { amount currencyCode }
      tracked
    }
  }
}
```

## Session Tracking

**Claude MUST emit the following output at each stage. This is mandatory.**

**On start**, emit:
```
╔══════════════════════════════════════════════╗
║  SKILL: Return Cost Attribution              ║
║  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):
```
══════════════════════════════════════════════
RETURN COST ATTRIBUTION  (<days_back> days, group: <group_by>)
  Returns analyzed:    <n>
  Total return cost:   $<amount>  (refund <pct>%, shipping <pct>%, COGS <pct>%, labor <pct>%)

  Top cost drivers:
    <group>   Returns: <n>  Total: $<n>  Avg: $<n>  Top reason: <reason>
  Output: return_cost_<date>.csv
══════════════════════════════════════════════
```

For `format: json`, emit:
```json
{
  "skill": "return-cost-attribution",
  "store": "<domain>",
  "period_days": 90,
  "group_by": "reason",
  "returns_analyzed": 0,
  "totals": {
    "total_cost": 0, "refund": 0, "shipping_loss": 0,
    "cogs_writeoff": 0, "restocking_labor": 0, "currency": "USD"
  },
  "groups": [],
  "output_file": "return_cost_<date>.csv"
}
```

## Output Format
CSV file `return_cost_<YYYY-MM-DD>.csv` with columns:
`group_key`, `return_count`, `units`, `refund_amount`, `shipping_loss`, `cogs_writeoff`, `restocking_labor`, `total_cost`, `avg_cost_per_return`, `top_return_reason`, `currency`

## Error Handling
| Error | Cause | Recovery |
|-------|-------|----------|
| `THROTTLED` | API rate limit exceeded | Wait 2 seconds, retry up to 3 times |
| Missing `unitCost` | Cost not recorded | Treat COGS as 0 and flag the row |
| Refund not yet processed | Customer not yet refunded | Use line item discounted total as estimate |
| Multiple refunds per return | Partial refund history | Sum refunds tied to the return's line items |
| No shipping cost | Free shipping | Shipping loss = 0 |

## Best Practices
- Use `group_by: reason_x_product` to surface lethal combos like `DEFECTIVE × <hero SKU>` — supplier-quality issues addressable at the source.
- Re-run after `unitCost` updates; stale cost most often skews COGS write-off.
- Pair with `return-reason-analysis` to compare "what returns most" with "what costs most" — they often diverge.

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