Install
$ agentstack add skill-40rty-ai-shopify-admin-skills-shopify-admin-agentic-product-jsonld-backfill ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Purpose
AI shopping agents read a product's structured data (the fields Shopify themes emit as schema.org/Product JSON-LD) to confirm price, availability, and identity. Missing barcodes (GTIN), SKUs, vendor, or product type leave the listing ambiguous — so the agent skips it or recommends a competitor whose data is complete. This skill finds products/variants with those gaps and backfills them: vendor and product type at the product level, barcode/SKU at the variant level. Fixes the agentiq.report findings product-schema-jsonld, gtin-sku-pdp, and variant-metadata.
Prerequisites
- Authenticated Shopify CLI session (
shopify auth login --store) - Required API scopes:
read_products,write_products
Parameters
All skills accept these universal parameters:
| Parameter | Type | Required | Default | Description | |-----------|--------|----------|---------|-------------| | store | string | yes | — | Store domain (e.g., mystore.myshopify.com) | | format | string | no | human | Output format: human (default) or json | | dry_run | bool | no | false | Preview mutations without executing |
Skill-specific parameters:
| Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | collectionid | string | no | — | Limit to a collection GID (else whole catalog) | | tag | string | no | — | Limit to a product tag | | setvendor | string | no | — | Vendor to apply where missing (else only reports) | | setproducttype | string | no | — | Product type to apply where missing | | barcodes_csv | string | no | — | Path to a CSV of sku,barcode to map GTINs onto matching variants | | fields | string | no | all | Comma list of fields to backfill: vendor,product_type,barcode,sku |
Safety
> ⚠️ Step 3 (productUpdate) and Step 4 (productVariantsBulkUpdate) write live product/variant data. Barcodes and SKUs are matched from your barcodes_csv; a wrong mapping mislabels a product's identity to every agent. Always run dry_run: true first and verify the change set CSV. This skill never overwrites a field that already has a value — it only fills blanks.
Workflow Steps
- OPERATION:
products— query
Inputs: first: 250, optional query: "tag:''" or collection filter; fields vendor, productType, variants{ id sku barcode }; paginate until hasNextPage: false. Expected output: Products/variants with missing target fields.
- COMPUTE (no API): build the change set — only blank fields, joined to
barcodes_csvby SKU for barcodes. Emit the preview CSV.
- OPERATION:
productUpdate— mutation
Inputs: per product { id, vendor?, productType? } (only where blank and a value is supplied). Expected output: Updated product; collect userErrors.
- OPERATION:
productVariantsBulkUpdate— mutation
Inputs: per product productId + variants: [{ id, barcode?, inventoryItem: { sku? } }] for blank variant fields. Expected output: Updated variants; collect userErrors across batches.
GraphQL Operations
# products:query — validated against api_version 2025-01
query BackfillProducts($first: Int!, $after: String, $query: String) {
products(first: $first, after: $after, query: $query) {
edges {
node {
id
title
vendor
productType
variants(first: 100) {
edges { node { id sku barcode } }
}
}
}
pageInfo { hasNextPage endCursor }
}
}
# productUpdate:mutation — validated against api_version 2025-01
mutation BackfillProductFields($input: ProductInput!) {
productUpdate(input: $input) {
product { id vendor productType }
userErrors { field message }
}
}
# productVariantsBulkUpdate:mutation — validated against api_version 2025-01
mutation BackfillVariantFields($productId: ID!, $variants: [ProductVariantsBulkInput!]!) {
productVariantsBulkUpdate(productId: $productId, variants: $variants) {
productVariants { id sku barcode }
userErrors { field message }
}
}
Session Tracking
Claude MUST emit the following output at each stage. This is mandatory.
On start, emit:
╔══════════════════════════════════════════════╗
║ SKILL: ║
║ Store: ║
║ Started: ║
╚══════════════════════════════════════════════╝
After each step, emit:
[N/TOTAL]
→ Params:
→ Result:
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
:
Errors: 0
Output:
══════════════════════════════════════════════
For format: json, emit:
{
"skill": "",
"store": "",
"started_at": "",
"completed_at": "",
"dry_run": false,
"steps": [
{
"step": 1,
"operation": "",
"type": "query",
"params_summary": "",
"result_summary": "",
"skipped": false
}
],
"outcome": {
"metric_key": 0,
"errors": 0,
"output_file": null
}
}
Output Format
human: counts of products/variants updated per field + a CSV of every change (product, variant, field, old, new). json: { products_updated, variants_updated, by_field{...}, errors, output_file }.
Error Handling
| Error | Cause | Recovery | |-------|-------|----------| | THROTTLED | API rate limit | Wait 2s, retry up to 3 times | | userErrors non-empty | Invalid barcode/SKU format or duplicate | Log message, skip that variant, continue | | SKU not in CSV | No mapping supplied for that variant | Leave barcode blank, report it as still-missing |
Best Practices
- Run
shopify-admin-agentic-readiness-auditfirst to size the gap, thendry_run: truehere to review the exact change set. - Barcodes are GTIN/UPC/EAN — get them from your supplier, never invent them. A wrong GTIN is worse than a blank one.
- This skill only fills blanks; to correct existing-but-wrong values use
shopify-admin-bulk-price-adjustment-style targeted edits instead. - Pair with
shopify-admin-agentic-metafields-setup— barcodes power JSON-LD identity, metafields power agent filtering; you usually want both.
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.
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Versions
- v0.1.0 Imported from the upstream source.