Shopify Catalog Cleanup

Shopify Catalog Cleanup

Fixing the debris an audit found. This is the mutating counterpart to shopify-catalog-audit (which finds problems) and shopify-seo-metadata (which fills missing metadata). Everything here writes to the catalog, so the whole skill is built around one rule: preview the count, then mutate.

Store access

Lane A: custom-app token (scriptable). In Shopify admin: Settings → Apps and sales channels → Develop apps → create an app → grant read_products and write_products, install, copy the Admin API access token. Export it; never write it to a committed file:

export SHOPIFY_STORE="your-store.myshopify.com"
export SHOPIFY_ACCESS_TOKEN="<your Admin API access token>"   # env, not disk

curl -s "https://$SHOPIFY_STORE/admin/api/2025-07/graphql.json" \
  -H "X-Shopify-Access-Token: $SHOPIFY_ACCESS_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"query":"{ shop { name } }"}'

Lane B: Shopify CLI OAuth (no stored token). shopify store auth --store $SHOPIFY_STORE --scopes read_products,write_products then shopify store execute. Good for token-less stores where the owner logs in interactively.

Toolkit preflight. Lane B rides on the Shopify CLI: run shopify version first and install it if missing. For the full Admin GraphQL schema and validated execution, pair this skill with Shopify's official AI toolkit plugin. In Claude Code, check claude plugin list; if it isn't there:

claude plugin marketplace add Shopify/Shopify-AI-Toolkit
claude plugin install shopify-plugin@shopify-ai-toolkit

Recommended, not required: Lane A needs only curl and a token. The toolkit gives your agent the API; this skill gives it the playbook.

The one rule: preview count, then mutate

Every recipe in references/recipes.md pairs a read-only count/preview query with the mutation it feeds. The discipline is not optional:

1. Run the count first. products(query:"…") with a filter returns count and a page of titles. Read them.
2. Sanity-check the number against expectation. If you expected ~40 dead products and the count says 900, stop and re-scope: your filter is wrong, not the store. A count far above expectation is a bug in your query.
3. Only then mutate, and prefer the reversible path (below).

Non-destructive doctrine

• Archive, never delete. Archiving a product (status: ARCHIVED) hides it from the storefront and channels but keeps the record, its handle, its history, and its URL-redirect potential. It is fully reversible: flip status back to ACTIVE or DRAFT. Deletion is not reversible: the product, its variants, and its metafields are gone. Default to archive; only delete when the owner explicitly asks and understands it is permanent.
• Tag what you touch. When you bulk-archive, add a dated tag (archived-2026-07-05) in the same mutation. That tag is your undo list: to reverse, query tag:archived-2026-07-05 and set status back. Without it you cannot cleanly separate your batch from products that were already archived.
• Read before you write. A read query is cheap; an unscoped mutation is not reversible. Verify a write landed by re-reading the object through the Admin API, not the storefront (the storefront is CDN-cached and lies about freshness).
• Never print or commit the Admin API access token.

Recipes, not scripts

The GraphQL blocks in the reference are copy-and-adapt starting points: your agent writes throwaway code per engagement against the current schema, runs it, discards it. Bulk mutations should batch and respect throttling: read the throttleStatus in the extensions block and back off when currentlyAvailable drops, rather than hammering a fixed rate.

Three fix classes

1. Bulk-archiving dead products

Design the criteria before you touch anything. Common "dead" signals, combined with AND (a product is rarely dead on one signal alone):

• Zero total inventory across all variants, and
• Zero sales in a trailing window (e.g. 12 months), and
• Created/updated long enough ago to not be a new launch, and
• Not in a collection you care about, or already tagged discontinued.

Turn that into a products(query: …) search filter, run the count query, read the sample titles, confirm the number is in the ballpark you expected, then run productUpdate to set status: ARCHIVED and append the dated tag. The unarchive path is the same query on your tag, flipping status back. Recipes: references/recipes.md.

2. Orphaned metafield debris (the ghost-star class)

Classic symptom: a store uninstalled a product-review app (Shopify's own Product Reviews is the usual culprit), but the theme still renders empty star ratings on every product. The app left its metafields behind: the spr.reviews field the Product Reviews app wrote, plus a reviews namespace holding reviews.rating and reviews.rating_count. The theme's star snippet reads them, finds 0, and paints five empty stars.

Fix safely:

1. Confirm the app is truly gone. Check Settings → Apps; the namespace must belong to an app that is uninstalled, not merely paused. Deleting metafields an installed app owns will just have the app rewrite them.
2. Inventory the orphaned namespaces. Query the product metafield definitions and a sample of products for every suspect namespace (spr and reviews for the Product Reviews app) so you know exactly which namespace.key pairs you are removing and how many products carry them.
3. Delete via metafieldsDelete, keyed by owner GID + namespace + key, covering both spr.reviews and the reviews.rating / reviews.rating_count fields. Preview the affected-count first, same as archiving; batch the identifiers to stay under rate/cost limits.
4. Re-read a few products to confirm the fields are gone, then reload the storefront product: the empty stars should be gone (the theme snippet may also need its now-dead reference removed; flag that to whoever owns the theme).

Matrixify warning: a blank cell in a Matrixify update deletes that metafield, it does not skip it. That is a footgun for accidental deletion and a tool for deliberate bulk removal: either way, know which you are doing. For spreadsheet-driven bulk work and that trap, see shopify-matrixify.

3. HTML artifacts in descriptions

Editors, app injections, and copy-paste leave residue in descriptionHtml: double-nested <strong><strong>…, whole paragraphs wrapped in bold, empty <p></p> / <span></span> tags, stray inline styles. Detect cheaply with an index scan (pull descriptionHtml for the scope, regex for the artifact patterns) rather than eyeballing products one by one. Fix by rewriting descriptionHtml per product via productUpdate: a targeted string transform, not a from-scratch rewrite that would lose real formatting.

Log old and new for every rewrite. As you go, write each rewrite (product id, old descriptionHtml, new descriptionHtml, status) to a CSV, the same discipline shopify-seo-metadata mandates for meta writes. That log is two things: your diff review (read a sample of old→new pairs before declaring done) and your only undo list. Archiving gets a dated tag to query for reversal; a rewrite has nothing, so without the log a bad transform is unrecoverable. This matters downstream too: skills that generate from body HTML (SEO meta, for one) inherit whatever a bad rewrite left behind.

Post-edit scan doctrine. After ANY bulk content edit, sweep the affected scope again for residue: double-bold, orphaned tags, half-applied transforms, before you declare done. A bulk regex fix routinely leaves a new artifact on the 3% of products whose markup didn't match your assumption. The passing re-scan is the evidence; "the transform ran" is not.

References

• references/recipes.md: count-before-mutate archive query + mutation, metafield-namespace inventory + metafieldsDelete, description-artifact scan + safe rewrite.

Provenance and maintenance

Last verified: 2026-07-05. GraphQL pinned to Admin API 2025-07; Shopify deprecates versions on a rolling quarterly schedule, so verify against shopify.dev before trusting a version-specific claim. Read-only re-verification a stranger can run (a metafield-namespace inventory and an archived-product count, both non-mutating):

# how many products are already archived, and a metafield namespace sample
curl -s "https://$SHOPIFY_STORE/admin/api/2025-07/graphql.json" \
  -H "X-Shopify-Access-Token: $SHOPIFY_ACCESS_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"query":"{ productsCount(query:\"status:archived\") { count } products(first:5) { nodes { title metafields(first:20) { nodes { namespace key } } } } }"}'

Canonical docs: productUpdate, metafieldsDelete. These skills capture operational lessons the docs don't; they are not a replacement for the reference.