Identify orders at risk of generating WISMO support tickets: shipped orders with stale tracking, and unfulfilled orders past their SLA window.
Scanned 5/28/2026
Install via CLI
openskills install 40RTY-ai/shopify-admin-skills---
name: shopify-admin-wismo-bulk-status-report
role: customer-support
description: "Identify orders at risk of generating WISMO support tickets: shipped orders with stale tracking, and unfulfilled orders past their SLA window."
toolkit: shopify-admin, shopify-admin-execution
api_version: "2025-01"
graphql_operations:
- orders:query
status: stable
compatibility: Claude Code, Cursor, Codex, Gemini CLI
---
## Purpose
Generates a bulk report of orders most likely to generate "Where Is My Order?" (WISMO) support tickets — shipped orders whose tracking hasn't updated in N days, and unfulfilled orders sitting past a configurable SLA. According to industry research, WISMO accounts for ~18% of all incoming support requests, making proactive identification a direct ops capacity investment. Read-only. Replaces manual order-by-order admin scanning or helpdesk searches. The CSV output can be used to proactively contact customers before they contact you.
## Prerequisites
- `shopify auth login --store <domain>`
- API scopes: `read_orders`
## 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` |
| dry_run | bool | no | false | Preview operations without executing mutations |
| unfulfilled_sla_days | integer | no | 3 | Flag unfulfilled orders older than this many days |
| stale_tracking_days | integer | no | 5 | Flag shipped orders where the last fulfillment was created more than this many days ago (proxy for stale tracking) |
| limit | integer | no | 250 | Max orders per page |
## Workflow Steps
1. **OPERATION:** `orders` — query (unfulfilled at-risk)
**Inputs:** `first: <limit>`, `query: "fulfillment_status:unfulfilled created_at:<='<NOW minus unfulfilled_sla_days>'"`, sort by `CREATED_AT` ascending
**Expected output:** Orders unfulfilled past SLA window with `name`, `createdAt`, `customer`, `displayFulfillmentStatus`; label as `UNFULFILLED_OVERDUE`
2. **OPERATION:** `orders` — query (shipped but potentially stale)
**Inputs:** `first: <limit>`, `query: "fulfillment_status:shipped updated_at:<='<NOW minus stale_tracking_days>'"`, sort by `UPDATED_AT` ascending
**Expected output:** Shipped orders not updated recently with `name`, `createdAt`, `fulfillments.createdAt`, `fulfillments.trackingInfo`; label as `SHIPPED_STALE_TRACKING`
## GraphQL Operations
```graphql
# orders:query — validated against api_version 2025-01
query WismoOrders($first: Int!, $after: String, $query: String) {
orders(first: $first, after: $after, query: $query, sortKey: CREATED_AT) {
edges {
node {
id
name
createdAt
updatedAt
displayFulfillmentStatus
displayFinancialStatus
customer {
id
firstName
lastName
defaultEmailAddress {
emailAddress
}
}
shippingAddress {
city
province
country
}
fulfillments {
createdAt
status
trackingInfo {
number
url
company
}
}
totalPriceSet {
shopMoney { amount currencyCode }
}
}
}
pageInfo {
hasNextPage
endCursor
}
}
}
```
## Session Tracking
**Claude MUST emit the following output at each stage. This is mandatory.**
**On start**, emit:
```
╔══════════════════════════════════════════════╗
║ SKILL: wismo-bulk-status-report ║
║ 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):
```
══════════════════════════════════════════════
OUTCOME SUMMARY
Unfulfilled overdue orders: <n>
Shipped stale-tracking orders: <n>
Total at-risk orders: <n>
Errors: 0
Output: wismo-report-<YYYY-MM-DD>.csv
══════════════════════════════════════════════
```
For `format: json`, emit:
```json
{
"skill": "wismo-bulk-status-report",
"store": "<domain>",
"started_at": "<ISO8601>",
"completed_at": "<ISO8601>",
"dry_run": false,
"steps": [
{ "step": 1, "operation": "WismoOrders", "type": "query", "params_summary": "fulfillment_status:unfulfilled, sla_days: <n>, limit: <n>", "result_summary": "<n> orders", "skipped": false },
{ "step": 2, "operation": "WismoOrders", "type": "query", "params_summary": "fulfillment_status:shipped, stale_days: <n>, limit: <n>", "result_summary": "<n> orders", "skipped": false }
],
"outcome": {
"unfulfilled_overdue_count": 0,
"shipped_stale_count": 0,
"total_at_risk": 0,
"errors": 0,
"output_file": "wismo-report-<YYYY-MM-DD>.csv"
}
}
```
## Output Format
CSV file `wismo-report-<YYYY-MM-DD>.csv` with columns: `risk_type`, `order_name`, `customer_email`, `order_date`, `days_waiting`, `fulfillment_status`, `tracking_number`, `tracking_company`, `shipping_city`, `shipping_country`.
Two sections in the CSV (separated by `risk_type` column value): `UNFULFILLED_OVERDUE` and `SHIPPED_STALE_TRACKING`. For human format, also shows a summary table before the CSV path.
## Error Handling
| Error | Cause | Recovery |
|-------|-------|----------|
| No orders returned | All orders are within SLA / recently updated | Good news — no WISMO risk detected |
| Very large result set | High order volume or wide SLA window | Narrow date range or reduce `unfulfilled_sla_days` |
| `customer` is null | Guest checkout order | Order name and tracking still included — email column will be empty |
| Rate limit (429) | Many pages of orders | Reduce `limit` to 100 |
## Best Practices
1. Run this report daily during your morning ops review alongside `fulfillment-status-digest` — together they cover both the ops queue and the customer-facing risk.
2. Sort the CSV by `days_waiting` descending to prioritize outreach to the most overdue orders first.
3. For `UNFULFILLED_OVERDUE` orders, forward to the `fulfillment-status-digest` skill to understand why they haven't been fulfilled and use `order-hold-and-release` if needed.
4. For `SHIPPED_STALE_TRACKING` orders, check if the carrier tracking URL shows movement — if it's genuinely stalled, proactive outreach reduces ticket volume significantly.
5. Use `format: json` to pipe the output into a Slack alert or CRM automation that creates follow-up tasks for your support team.
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