/shopify-admin-product-lifecycle-manager
Bulk transition products through DRAFT → ACTIVE → ARCHIVED status for seasonal launches and sunsetting.
$ npx -y skills add 40rty-ai/shopify-admin-skills --skill shopify-admin-product-lifecycle-manager --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/shopify-admin-product-lifecycle-manager
Context preview
The summary Claude sees to decide when to auto-load this skill.
Bulk transition products through DRAFT → ACTIVE → ARCHIVED status for seasonal launches and sunsetting.
SKILL.md
shopify-admin-product-lifecycle-manager.SKILL.mdname: shopify-admin-product-lifecycle-manager
role: merchandising
description: "Bulk transition products through DRAFT → ACTIVE → ARCHIVED status for seasonal launches and sunsetting."
toolkit: shopify-admin, shopify-admin-execution
api_version: "2025-01"
graphql_operations:
- products:query
- productUpdate:mutation
status: stable
compatibility: Claude Code, Cursor, Codex, Gemini CLI
Purpose
Queries products matching a tag, vendor, collection, or status filter and bulk-transitions them to a target status (DRAFT, ACTIVE, or ARCHIVED). Used for seasonal launches (DRAFT → ACTIVE), end-of-season sunsetting (ACTIVE → ARCHIVED), and pre-launch staging (creating as DRAFT, activating on a date).
Prerequisites
- Authenticated Shopify CLI session: `shopify store auth --store <domain> --scopes read_products,write_products`
- API scopes: `read_products`, `write_products`
Parameters
| Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | store | string | yes | — | Store domain (e.g., mystore.myshopify.com) | | filter | string | yes | — | Product filter query (e.g., `tag:summer-2026`, `vendor:Nike`, `status:draft`) | | target_status | string | yes | — | Target status: `ACTIVE`, `DRAFT`, or `ARCHIVED` | | dry_run | bool | no | true | Preview products without executing mutations | | format | string | no | human | Output format: `human` or `json` |
Safety
> ⚠️ ARCHIVED products are hidden from all sales channels and cannot be purchased. ACTIVE products are immediately visible to customers. Run with `dry_run: true` to review the product list before committing — especially for ARCHIVED transitions which are hard to reverse in bulk.
Workflow Steps
1. **OPERATION:** `products` — query **Inputs:** `query: <filter>`, `first: 250`, pagination cursor **Expected output:** Products with `id`, `title`, `status`, `tags`; paginate until `hasNextPage: false`
2. Filter to products NOT already in `target_status` — skip those already correct
3. **OPERATION:** `productUpdate` — mutation **Inputs:** `id: <product_id>`, `status: <target_status>` **Expected output:** `product { id, title, status }`, `userErrors`
GraphQL Operations
# products:query — validated against api_version 2025-01
query ProductsByFilter($query: String!, $after: String) {
products(first: 250, after: $after, query: $query) {
edges {
node {
id
title
status
vendor
tags
publishedAt
}
}
pageInfo {
hasNextPage
endCursor
}
}
}# productUpdate:mutation — validated against api_version 2025-01
mutation ProductUpdateStatus($input: ProductInput!) {
productUpdate(input: $input) {
product {
id
title
status
}
userErrors {
field
message
}
}
}Session Tracking
**Claude MUST emit the following output at each stage. This is mandatory.**
**On start**, emit:
╔══════════════════════════════════════════════╗
║ SKILL: Product Lifecycle Manager ║
║ Store: <store domain> ║
║ Started: <YYYY-MM-DD HH:MM UTC> ║
╚══════════════════════════════════════════════╝
**After each step**, emit:
[N/TOTAL] <QUERY|MUTATION> <OperationName>
→ Params: <brief summary of key inputs>
→ Result: <count or outcome>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
Products matched: <n>
Already at target: <n> (skipped)
Status updated: <n>
Errors: <n>
Output: lifecycle_update_<date>.csv
══════════════════════════════════════════════
For `format: json`, emit:
{
"skill": "product-lifecycle-manager",
"store": "<domain>",
"started_at": "<ISO8601>",
"completed_at": "<ISO8601>",
"dry_run": true,
"filter": "<query>",
"target_status": "ACTIVE",
"outcome": {
"matched": 0,
"skipped_already_correct": 0,
"updated": 0,
"errors": 0,
"output_file": "lifecycle_update_<date>.csv"
}
}Output Format
CSV file `lifecycle_update_<YYYY-MM-DD>.csv` with columns: `product_id`, `title`, `previous_status`, `new_status`, `vendor`, `tags`
Error Handling
| Error | Cause | Recovery | |-------|-------|----------| | `THROTTLED` | API rate limit exceeded | Wait 2 seconds, retry up to 3 times | | `userErrors` on productUpdate | Product locked or invalid state | Log error, skip product, continue | | No products match filter | Filter too narrow | Exit with 0 matches, suggest broadening filter |
Best Practices
- Use tags to mark seasonal batches before running (e.g., tag products with `launch:2026-05` before activating them) so the filter is precise.
- ARCHIVED status removes products from all channels including the storefront, POS, and buy buttons — confirm this is the intent before running at scale.
- For large catalogs (500+ products), rate limiting will slow execution — the skill retries automatically but large batches may take several minutes.
- Pair with `product-data-completeness-score` before activating DRAFT products to ensure they have all required fields.
Read more
name: shopify-admin-product-lifecycle-manager role: merchandising description: "Bulk transition products through DRAFT → ACTIVE → ARCHIVED status for seasonal launches and sunsetting." toolkit: shopify-admin, shopify-admin-execution api_version: "2025-01" graphql_operations: - products:query - productUpdate:mutation status: stable compatibility: Claude Code, Cursor, Codex, Gemini CLI
Purpose
Queries products matching a tag, vendor, collection, or status filter and bulk-transitions them to a target status (DRAFT, ACTIVE, or ARCHIVED). Used for seasonal launches (DRAFT → ACTIVE), end-of-season sunsetting (ACTIVE → ARCHIVED), and pre-launch staging (creating as DRAFT, activating on a date).
Prerequisites
- Authenticated Shopify CLI session: `shopify store auth --store <domain> --scopes read_products,write_products`
- API scopes: `read_products`, `write_products`
Parameters
| Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | store | string | yes | — | Store domain (e.g., mystore.myshopify.com) | | filter | string | yes | — | Product filter query (e.g., `tag:summer-2026`, `vendor:Nike`, `status:draft`) | | target_status | string | yes | — | Target status: `ACTIVE`, `DRAFT`, or `ARCHIVED` | | dry_run | bool | no | true | Preview products without executing mutations | | format | string | no | human | Output format: `human` or `json` |
Safety
> ⚠️ ARCHIVED products are hidden from all sales channels and cannot be purchased. ACTIVE products are immediately visible to customers. Run with `dry_run: true` to review the product list before committing — especially for ARCHIVED transitions which are hard to reverse in bulk.
Workflow Steps
1. **OPERATION:** `products` — query **Inputs:** `query: <filter>`, `first: 250`, pagination cursor **Expected output:** Products with `id`, `title`, `status`, `tags`; paginate until `hasNextPage: false`
2. Filter to products NOT already in `target_status` — skip those already correct
3. **OPERATION:** `productUpdate` — mutation **Inputs:** `id: <product_id>`, `status: <target_status>` **Expected output:** `product { id, title, status }`, `userErrors`
GraphQL Operations
# products:query — validated against api_version 2025-01
query ProductsByFilter($query: String!, $after: String) {
products(first: 250, after: $after, query: $query) {
edges {
node {
id
title
status
vendor
tags
publishedAt
}
}
pageInfo {
hasNextPage
endCursor
}
}
}# productUpdate:mutation — validated against api_version 2025-01
mutation ProductUpdateStatus($input: ProductInput!) {
productUpdate(input: $input) {
product {
id
title
status
}
userErrors {
field
message
}
}
}Session Tracking
**Claude MUST emit the following output at each stage. This is mandatory.**
**On start**, emit:
╔══════════════════════════════════════════════╗ ║ SKILL: Product Lifecycle Manager ║ ║ Store: <store domain> ║ ║ Started: <YYYY-MM-DD HH:MM UTC> ║ ╚══════════════════════════════════════════════╝
**After each step**, emit:
[N/TOTAL] <QUERY|MUTATION> <OperationName>
→ Params: <brief summary of key inputs>
→ Result: <count or outcome>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 Products matched: <n> Already at target: <n> (skipped) Status updated: <n> Errors: <n> Output: lifecycle_update_<date>.csv ══════════════════════════════════════════════
For `format: json`, emit:
{
"skill": "product-lifecycle-manager",
"store": "<domain>",
"started_at": "<ISO8601>",
"completed_at": "<ISO8601>",
"dry_run": true,
"filter": "<query>",
"target_status": "ACTIVE",
"outcome": {
"matched": 0,
"skipped_already_correct": 0,
"updated": 0,
"errors": 0,
"output_file": "lifecycle_update_<date>.csv"
}
}Output Format
CSV file `lifecycle_update_<YYYY-MM-DD>.csv` with columns: `product_id`, `title`, `previous_status`, `new_status`, `vendor`, `tags`
Error Handling
| Error | Cause | Recovery | |-------|-------|----------| | `THROTTLED` | API rate limit exceeded | Wait 2 seconds, retry up to 3 times | | `userErrors` on productUpdate | Product locked or invalid state | Log error, skip product, continue | | No products match filter | Filter too narrow | Exit with 0 matches, suggest broadening filter |
Best Practices
- Use tags to mark seasonal batches before running (e.g., tag products with `launch:2026-05` before activating them) so the filter is precise.
- ARCHIVED status removes products from all channels including the storefront, POS, and buy buttons — confirm this is the intent before running at scale.
- For large catalogs (500+ products), rate limiting will slow execution — the skill retries automatically but large batches may take several minutes.
- Pair with `product-data-completeness-score` before activating DRAFT products to ensure they have all required fields.
Community-maintained AI agent skills for operating Shopify stores — workflows, optimization, reports and more
Other skills on shopify-admin-skills.
- /shopify-admin-agentic-crawler-access
Edit the theme's robots.txt.liquid to explicitly allow AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended, OAI-SearchBot, Amazonbot) so AI assistants are permitted to read the catalog.
Open skill - /shopify-admin-agentic-description-enrichment
Rewrite thin product descriptions into structured, fact-rich copy (materials, fit, use-cases, the words shoppers actually type) so AI agents have something concrete to quote and match.
Open skill - /shopify-admin-agentic-image-alt-text
Generate and set descriptive alt text on product images so AI agents (which can't 'see' pixels) can understand and recommend what each product looks like.
Open skill - /shopify-admin-agentic-llms-txt
Generate and publish an /llms.txt guide (brand summary, flagship products, key policies, contact) via a theme template so AI assistants get a curated, machine-readable map of the store.
Open skill - /shopify-admin-agentic-metafields-setup
Define and populate agentic-commerce metafields (material, attributes, key features, specs, sizing) so AI agents can filter and match products to specific shopper requirements.
Open skill - /shopify-admin-agentic-organization-schema
Inject an Organization JSON-LD block (name, logo, sameAs social links, contactPoint) into the theme so AI agents can verify the store is a real, trusted brand and link it to its public identity.
Open skill

