Merchandising
Zmienia dane w sklepie — wymagany dry_run
Product Data Completeness Score
Score how complete each product is on description, images and metadata.
BeginnerAPI 2025-01
Command
bash
shopify-admin-skills:product-data-completeness-score store=your-store.myshopify.com### name
Product Data Completeness Score — 0–100 Rating per SKU
### oneLiner
Scores every active product on data completeness and pinpoints exactly which fields are holding down the rating.
### whenToUse
- Before activating DRAFT products, to confirm they have a description, images, and SEO fields filled in.
- After importing a catalog from a new supplier, to scope the depth of data gaps immediately.
- Monthly, to track catalog quality trends and measure the impact of a content sprint.
### howToRun
```
Run skill: shopify-admin-product-data-completeness-score
Store: yourstore.myshopify.com
status_filter: active
required_metafields: ["custom.material"]
```
### whatYouGet
A CSV file `completeness_YYYY-MM-DD.csv` with columns: `product_id`, `title`, `score`, `has_description`, `image_count`, `has_seo_title`, `has_seo_description`, `has_barcode`, `has_cost`, `has_weight`, `missing_metafields`. Products scoring below 50 are missing foundational content (description or images) and should be fixed before activation. Configure `required_metafields` for your store's specific needs — for example `custom.material` for apparel.
### polishContext
### safetyNote
Bazuje na open-source 40RTY-ai/shopify-admin-skills (MIT), rozszerzone o kontekst polskiego rynku przez Dawida Gaca.