Shopify Admin Discount Hygiene Cleanup

Purpose

Audits the discount catalog for expired codes, codes with zero redemptions, and duplicate code prefixes. Discount sprawl accumulates over months of campaigns and makes the admin difficult to navigate. Optionally deletes flagged codes. Replaces manual discount cleanup and builds on the discount-ab-analysis skill with a write step.

Prerequisites

• Authenticated Shopify CLI session: shopify store auth --store <domain> --scopes read_discounts,write_discounts
• API scopes: read_discounts, write_discounts

Parameters

Safety

⚠️ discountCodeDelete permanently removes discount codes. Deleted codes cannot be recovered. Customers who received a deleted code will find it invalid. Run with dry_run: true to review the flagged list before committing. Always check that expired codes are not referenced in active email campaigns before deleting.

Workflow Steps

1. OPERATION: discountNodes — query Inputs: first: 250, select discount { ... on DiscountCodeBasic { codes, usageLimit, asyncUsageCount, endsAt, status } }, pagination cursor Expected output: All discount codes with usage and expiry data; paginate until hasNextPage: false

2. Flag discounts matching: flag_expired (status = EXPIRED) and/or flag_zero_usage (asyncUsageCount == 0 AND created > zero_usage_min_age_days ago)

3. OPERATION: discountCodeDelete — mutation Inputs: id: <discount_node_id> Expected output: deletedCodeDiscountId, userErrors

GraphQL Operations

# discountNodes:query — validated against api_version 2025-01
query DiscountAudit($after: String) {
  discountNodes(first: 250, after: $after) {
    edges {
      node {
        id
        discount {
          ... on DiscountCodeBasic {
            title
            status
            createdAt
            endsAt
            asyncUsageCount
            usageLimit
            codes(first: 5) {
              edges {
                node {
                  id
                  code
                }
              }
            }
          }
          ... on DiscountCodeBxgy {
            title
            status
            createdAt
            endsAt
            asyncUsageCount
            usageLimit
          }
          ... on DiscountCodeFreeShipping {
            title
            status
            createdAt
            endsAt
            asyncUsageCount
            usageLimit
          }
        }
      }
    }
    pageInfo {
      hasNextPage
      endCursor
    }
  }
}

# discountCodeDelete:mutation — validated against api_version 2025-01
mutation DiscountCodeDelete($id: ID!) {
  discountCodeDelete(id: $id) {
    deletedCodeDiscountId
    userErrors {
      field
      message
    }
  }
}

Session Tracking

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

On start, emit:

╔══════════════════════════════════════════════╗
║  SKILL: Discount Hygiene Cleanup             ║
║  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>

If dry_run: true, prefix every mutation step with [DRY RUN] and do not execute it.

On completion, emit:

For format: human (default):

══════════════════════════════════════════════
OUTCOME SUMMARY
  Discounts scanned:     <n>
  Expired:               <n>
  Zero usage (> <n> days): <n>
  Total flagged:         <n>
  Deleted:               <n>
  Errors:                <n>
  Output:                discount_cleanup_<date>.csv
══════════════════════════════════════════════

For format: json, emit:

{
  "skill": "discount-hygiene-cleanup",
  "store": "<domain>",
  "started_at": "<ISO8601>",
  "dry_run": true,
  "outcome": {
    "scanned": 0,
    "flagged_expired": 0,
    "flagged_zero_usage": 0,
    "deleted": 0,
    "errors": 0,
    "output_file": "discount_cleanup_<date>.csv"
  }
}

Output Format

CSV file discount_cleanup_<YYYY-MM-DD>.csv with columns: discount_id, title, status, created_at, ends_at, usage_count, usage_limit, flag_reason, action

Error Handling

Best Practices

• Run quarterly — discount code sprawl accumulates quickly with seasonal campaigns.
• Check with your email marketing team before deleting zero-usage codes — they may be in a scheduled campaign that hasn't launched yet.
• Keep flag_zero_usage age at 30+ days to avoid deleting codes from recently launched campaigns.
• Automatic/percentage discounts (not code-based) are not cleaned up by this skill — those are managed separately.