Shopify Admin Vendor Consolidation

Purpose

Walks every product in the catalog, normalizes the vendor field, and clusters near-duplicates such as Acme, ACME, Acme Inc, and Acme (trailing whitespace). Surfaces a recommended canonical form per cluster and the count of products that would migrate. Vendor sprawl breaks vendor-based reports, navigation, and supplier reconciliation. Read-only — no mutations; output is the worklist for a follow-up consolidation.

Prerequisites

• Authenticated Shopify CLI session: shopify store auth --store --scopes read_products
• API scopes: read_products

Parameters

| Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | store | string | yes | — | Store domain (e.g., mystore.myshopify.com) | | similaritythreshold | float | no | 0.88 | Levenshtein-ratio threshold for clustering (0.0–1.0) | | minclustersize | integer | no | 2 | Only emit clusters with at least this many distinct vendor strings | | ignoresuffixes | string | no | "Inc,LLC,Ltd,Co,Corp" | Comma-separated company suffixes stripped before comparison | | status_filter | string | no | ALL | Product status to include: ACTIVE, DRAFT, ARCHIVED, or ALL | | format | string | no | human | Output format: human or json |

Safety

> ℹ️ Read-only skill — no mutations are executed. Safe to run at any time. The skill produces a recommendation worklist; consolidation must be applied through a separate, reviewed workflow.

Workflow Steps

1. OPERATION: products — query

Inputs: first: 250, query: , select vendor, id, title, status, pagination cursor Expected output: Every product with its vendor string; paginate until hasNextPage: false

1. Build a frequency map of distinct vendor strings → product count. Normalize each vendor with: trim whitespace, collapse multiple spaces, strip configured suffixes, lowercase for comparison.

1. Cluster vendor strings whose normalized form has a Levenshtein ratio above similarity_threshold. Pick canonical per cluster as the most-used variant; tie-break on shortest, then alphabetical.

1. Filter clusters with fewer than min_cluster_size distinct strings. Compute migration impact: number of products that would move to the canonical form.

1. Sort clusters by migration impact descending so the highest-leverage merges surface first.

GraphQL Operations

# products:query — validated against api_version 2025-01
query AllVendors($query: String, $after: String) {
  products(first: 250, after: $after, query: $query) {
    edges {
      node {
        id
        title
        vendor
        status
        productType
        updatedAt
      }
    }
    pageInfo {
      hasNextPage
      endCursor
    }
  }
}

Session Tracking

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

On start, emit:

╔══════════════════════════════════════════════╗
║  SKILL: Vendor Consolidation                 ║
║  Store:                        ║
║  Started:              ║
╚══════════════════════════════════════════════╝

After each step, emit:

[N/TOTAL]   
          → Params: 
          → Result: 

On completion, emit:

For format: human (default):

══════════════════════════════════════════════
VENDOR CONSOLIDATION REPORT
  Products scanned:        
  Distinct vendors:        
  Clusters detected:       
  Products to migrate:     

  Top clusters by impact:
    Canonical: ""  Variants:   Products: 
      ""  ()
      ""  ()
  Output: vendor_consolidation_.csv
══════════════════════════════════════════════

For format: json, emit:

{
  "skill": "vendor-consolidation",
  "store": "",
  "products_scanned": 0,
  "distinct_vendors": 0,
  "clusters": [
    {
      "canonical": "Acme",
      "variants": [
        { "value": "Acme", "products": 0 },
        { "value": "ACME", "products": 0 },
        { "value": "Acme Inc", "products": 0 }
      ],
      "products_to_migrate": 0
    }
  ],
  "output_file": "vendor_consolidation_.csv"
}

Output Format

CSV file vendor_consolidation_.csv with columns: cluster_id, canonical_vendor, variant_vendor, is_canonical, product_count, sample_product_id, sample_product_title, status

Error Handling

| Error | Cause | Recovery | |-------|-------|----------| | THROTTLED | API rate limit exceeded | Wait 2 seconds, retry up to 3 times | | Empty vendor field on product | Vendor never set | Bucket as cluster (unset), surface count separately | | Two valid distinct vendors collide on similarity | False positive (e.g., Apple vs Appel) | Lower similarity_threshold is unsafe; review cluster manually before applying | | Unicode-different but visually identical vendors | Smart-quote or non-breaking space | Normalization step strips these before comparison |

Best Practices

• Start with the default similarity_threshold: 0.88. Below 0.85, false positives multiply quickly.
• Manually review every cluster before applying — ABC Corp and ABC Co. may or may not be the same supplier in your books.
• Use ignore_suffixes to absorb legal-entity noise (Inc, LLC) which rarely changes the actual vendor identity.
• After review, drive consolidation via a separate update workflow (for example, an internal product-update script) and re-run this audit until clusters drop below min_cluster_size.
• Pair with product-data-completeness-score to track vendor-field cleanliness over time alongside other catalog quality metrics.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: 40RTY-ai
• Source: 40RTY-ai/shopify-admin-skills
• License: MIT
• Homepage: http://skills.40rty.ai

Install and usage instructions live in the source repository linked above.