--- name: shopify-admin-cogs-completeness-audit role: merchandising description: "Read-only: identifies products and variants that are missing inventoryItem.unitCost so margin and inventory valuation reports stay accurate." toolkit: shopify-admin, shopify-admin-execution api_version: "2025-01" graphql_operations: - productVariants:query - inventoryItems:query status: stable compatibility: Claude Code, Cursor, Codex, Gemini CLI --- ## Purpose Scans every variant in the catalog and surfaces those whose `inventoryItem.unitCost` is missing or zero. Cost of goods sold (COGS) is the foundation for margin reporting, profit-based pricing decisions, and inventory valuation — a single missing cost silently corrupts every downstream calculation. Read-only — no mutations. ## Prerequisites - Authenticated Shopify CLI session: `shopify store auth --store --scopes read_products,read_inventory` - API scopes: `read_products`, `read_inventory` ## Parameters | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | store | string | yes | — | Store domain (e.g., mystore.myshopify.com) | | status_filter | string | no | ACTIVE | Variant product status to audit: `ACTIVE`, `DRAFT`, `ARCHIVED`, or `ALL` | | vendor_filter | string | no | — | Optional vendor to scope the audit | | include_zero_cost | bool | no | true | Treat `unitCost = 0` as missing (recommended; zero cost is rarely intentional) | | only_stocked | bool | no | true | Limit to variants with `inventoryQuantity > 0` | | 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 flags missing data; remediation should happen through a follow-up workflow that you control. ## Workflow Steps 1. **OPERATION:** `productVariants` — query **Inputs:** `first: 250`, `query: `, select `sku`, `price`, `inventoryQuantity`, `inventoryItem { id }`, `product { title, vendor, status, productType }`, pagination cursor **Expected output:** All matching variants; paginate until `hasNextPage: false` 2. **OPERATION:** `inventoryItems` — query **Inputs:** Batched `inventoryItemIds` (≤100 per request) **Expected output:** `unitCost { amount, currencyCode }`, `tracked` 3. Filter to variants where `unitCost == null` or `unitCost.amount == 0` (when `include_zero_cost: true`). Compute potential margin gap as `price - 0 = price` for the missing-cost variants — this is the fictional margin downstream reports will show. 4. Summarize: count missing, % of catalog, total stock-value impact (`sum of inventoryQuantity * price` across missing rows since you cannot value them on cost). ## GraphQL Operations ```graphql # productVariants:query — validated against api_version 2025-01 query VariantsForCogsAudit($query: String, $after: String) { productVariants(first: 250, after: $after, query: $query) { edges { node { id sku title price inventoryQuantity product { id title vendor status productType } inventoryItem { id } } } pageInfo { hasNextPage endCursor } } } ``` ```graphql # inventoryItems:query — validated against api_version 2025-01 query InventoryItemCosts($ids: [ID!]!) { nodes(ids: $ids) { ... on InventoryItem { id tracked sku unitCost { amount currencyCode } } } } ``` ## Session Tracking **Claude MUST emit the following output at each stage. This is mandatory.** **On start**, emit: ``` ╔══════════════════════════════════════════════╗ ║ SKILL: COGS Completeness Audit ║ ║ Store: ║ ║ Started: ║ ╚══════════════════════════════════════════════╝ ``` **After each step**, emit: ``` [N/TOTAL] → Params: → Result: ``` **On completion**, emit: For `format: human` (default): ``` ══════════════════════════════════════════════ COGS COMPLETENESS AUDIT Variants audited: Missing unit cost: (%) Stocked + missing cost: Catalog value at risk: $ (priced, not costed) Top vendors by missing variants: Missing: Stocked: Output: cogs_audit_.csv ══════════════════════════════════════════════ ``` For `format: json`, emit: ```json { "skill": "cogs-completeness-audit", "store": "", "variants_audited": 0, "missing_cost": 0, "missing_cost_pct": 0, "stocked_missing": 0, "value_at_risk": 0, "currency": "USD", "output_file": "cogs_audit_.csv" } ``` ## Output Format CSV file `cogs_audit_.csv` with columns: `variant_id`, `inventory_item_id`, `sku`, `product_title`, `vendor`, `product_status`, `price`, `unit_cost`, `inventory_quantity`, `value_at_price`, `currency` ## Error Handling | Error | Cause | Recovery | |-------|-------|----------| | `THROTTLED` | API rate limit exceeded | Wait 2 seconds, retry up to 3 times | | `inventoryItem` is null | Variant has no inventory item (rare) | Skip, note in error count | | `unitCost.currencyCode` differs from store currency | Multi-currency cost capture | Treat as present; do not flag, surface currency mismatch separately | | All variants have costs | Healthy catalog | Exit with summary: 0 missing, 100% complete | ## Best Practices - Run monthly; whenever new vendors or product lines are onboarded, run on day one of activation to catch missing costs before margin reports are trusted. - Filter by `vendor_filter` to assign remediation work to the buyer responsible for that vendor's data. - Pair with `inventory-valuation-report` — that report will silently treat missing-cost SKUs as worthless inventory unless this audit is clean. - Treat `unitCost = 0` as missing by default. Genuine zero-cost SKUs (free samples, GWP) are rare; tag those with a `zero-cost-intentional` product tag and exclude them from the audit via `vendor_filter` or downstream filtering. - Use the CSV as a worklist: hand it to the merchandising team for cost capture, then re-run weekly until the missing count is zero.