/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.
$ npx -y skills add 40rty-ai/shopify-admin-skills --skill shopify-admin-agentic-description-enrichment --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-agentic-description-enrichment
Context preview
The summary Claude sees to decide when to auto-load this skill.
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.
SKILL.md
shopify-admin-agentic-description-enrichment.SKILL.mdname: shopify-admin-agentic-description-enrichment
role: agentic
description: "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."
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
audit_signals:
- listing-description-quality
- agentic-listing-schema
Purpose
When an AI agent decides whether to recommend a product, it quotes the description to justify the match. One-line or empty descriptions give it nothing — so it can't confirm the product fits the shopper's intent and moves on. This skill finds products with thin descriptions (below a character threshold or missing key attributes) and rewrites them into structured copy: a benefit-led opening line, then concrete facts (material, fit/sizing, dimensions, use-cases, care) drawn from the product's own metafields/options/type. Fixes `listing-description-quality` and strengthens `agentic-listing-schema`.
Prerequisites
- Authenticated Shopify CLI session (`shopify auth login --store <domain>`)
- 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 | |-----------|------|----------|---------|-------------| | collection_id | string | no | — | Limit to a collection GID | | tag | string | no | — | Limit to a product tag | | min_chars | int | no | 120 | Products with a plain-text description shorter than this are rewritten | | overwrite | bool | no | false | If false, only enrich products below `min_chars`; if true, restructure all targeted products | | brand_voice | string | no | — | Optional voice guidance (e.g., "plain, technical, no hype") |
Safety
> ⚠️ Step 3 (`productUpdate`) replaces `descriptionHtml` on live products. This is content the merchant may have hand-written. Always run `dry_run: true`, export the before/after, and have a human approve the rewrites before committing. Default only touches products under `min_chars`.
Workflow Steps
1. **OPERATION:** `products` — query **Inputs:** `first: 100`, optional filter; fields `descriptionHtml`, `title`, `productType`, `options`, `tags`, `metafields(first: 30)`; paginate. **Expected output:** Products whose stripped-text description is below `min_chars`, plus the structured facts available to enrich from.
2. **COMPUTE (no API):** for each thin product, draft `descriptionHtml`: a one-line benefit hook + a short facts list built ONLY from real product data (no invented specs), honoring `brand_voice`. Emit a before/after preview.
3. **OPERATION:** `productUpdate` — mutation **Inputs:** `{ id, descriptionHtml }` per approved product. **Expected output:** Updated product; collect `userErrors`.
GraphQL Operations
# products:query — validated against api_version 2025-01
query EnrichProducts($first: Int!, $after: String, $query: String) {
products(first: $first, after: $after, query: $query) {
edges {
node {
id
title
descriptionHtml
productType
tags
options { name values }
metafields(first: 30) { edges { node { namespace key value type } } }
}
}
pageInfo { hasNextPage endCursor }
}
}# productUpdate:mutation — validated against api_version 2025-01
mutation EnrichProductDescription($input: ProductInput!) {
productUpdate(input: $input) {
product { id descriptionHtml }
userErrors { field message }
}
}Session Tracking
**Claude MUST emit the following output at each stage. This is mandatory.**
**On start**, emit:
╔══════════════════════════════════════════════╗
║ SKILL: <skill name> ║
║ 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
<Metric label>: <value>
Errors: 0
Output: <filename or "none">
══════════════════════════════════════════════
For `format: json`, emit:
{
"skill": "<skill-slug>",
"store": "<domain>",
"started_at": "<ISO8601>",
"completed_at": "<ISO8601>",
"dry_run": false,
"steps": [
{
"step": 1,
"operation": "<OperationName>",
"type": "query",
"params_summary": "<string>",
"result_summary": "<string>",
"skipped": false
}
],
"outcome": {
"metric_key": 0,
"errors": 0,
"output_file": null
}
}Output Format
`human`: count enriched + a before/after CSV (`product, old_len, new_len, new_description`). `json`: `{ products_enriched, products_skipped, errors, output_file }`.
Error Handling
| Error | Cause | Recovery | |-------|-------|----------| | `THROTTLED` | API rate limit | Wait 2s, retry up to 3 times | | `userErrors` non-empty | Invalid HTML / field length | Log message, skip product, continue | | No facts to enrich from | Sparse product data | Skip; recommend running `shopify-admin-agentic-
Read more
name: shopify-admin-agentic-description-enrichment role: agentic description: "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." 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 audit_signals: - listing-description-quality - agentic-listing-schema
Purpose
When an AI agent decides whether to recommend a product, it quotes the description to justify the match. One-line or empty descriptions give it nothing — so it can't confirm the product fits the shopper's intent and moves on. This skill finds products with thin descriptions (below a character threshold or missing key attributes) and rewrites them into structured copy: a benefit-led opening line, then concrete facts (material, fit/sizing, dimensions, use-cases, care) drawn from the product's own metafields/options/type. Fixes `listing-description-quality` and strengthens `agentic-listing-schema`.
Prerequisites
- Authenticated Shopify CLI session (`shopify auth login --store <domain>`)
- 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 | |-----------|------|----------|---------|-------------| | collection_id | string | no | — | Limit to a collection GID | | tag | string | no | — | Limit to a product tag | | min_chars | int | no | 120 | Products with a plain-text description shorter than this are rewritten | | overwrite | bool | no | false | If false, only enrich products below `min_chars`; if true, restructure all targeted products | | brand_voice | string | no | — | Optional voice guidance (e.g., "plain, technical, no hype") |
Safety
> ⚠️ Step 3 (`productUpdate`) replaces `descriptionHtml` on live products. This is content the merchant may have hand-written. Always run `dry_run: true`, export the before/after, and have a human approve the rewrites before committing. Default only touches products under `min_chars`.
Workflow Steps
1. **OPERATION:** `products` — query **Inputs:** `first: 100`, optional filter; fields `descriptionHtml`, `title`, `productType`, `options`, `tags`, `metafields(first: 30)`; paginate. **Expected output:** Products whose stripped-text description is below `min_chars`, plus the structured facts available to enrich from.
2. **COMPUTE (no API):** for each thin product, draft `descriptionHtml`: a one-line benefit hook + a short facts list built ONLY from real product data (no invented specs), honoring `brand_voice`. Emit a before/after preview.
3. **OPERATION:** `productUpdate` — mutation **Inputs:** `{ id, descriptionHtml }` per approved product. **Expected output:** Updated product; collect `userErrors`.
GraphQL Operations
# products:query — validated against api_version 2025-01
query EnrichProducts($first: Int!, $after: String, $query: String) {
products(first: $first, after: $after, query: $query) {
edges {
node {
id
title
descriptionHtml
productType
tags
options { name values }
metafields(first: 30) { edges { node { namespace key value type } } }
}
}
pageInfo { hasNextPage endCursor }
}
}# productUpdate:mutation — validated against api_version 2025-01
mutation EnrichProductDescription($input: ProductInput!) {
productUpdate(input: $input) {
product { id descriptionHtml }
userErrors { field message }
}
}Session Tracking
**Claude MUST emit the following output at each stage. This is mandatory.**
**On start**, emit:
╔══════════════════════════════════════════════╗ ║ SKILL: <skill name> ║ ║ 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 <Metric label>: <value> Errors: 0 Output: <filename or "none"> ══════════════════════════════════════════════
For `format: json`, emit:
{
"skill": "<skill-slug>",
"store": "<domain>",
"started_at": "<ISO8601>",
"completed_at": "<ISO8601>",
"dry_run": false,
"steps": [
{
"step": 1,
"operation": "<OperationName>",
"type": "query",
"params_summary": "<string>",
"result_summary": "<string>",
"skipped": false
}
],
"outcome": {
"metric_key": 0,
"errors": 0,
"output_file": null
}
}Output Format
`human`: count enriched + a before/after CSV (`product, old_len, new_len, new_description`). `json`: `{ products_enriched, products_skipped, errors, output_file }`.
Error Handling
| Error | Cause | Recovery | |-------|-------|----------| | `THROTTLED` | API rate limit | Wait 2s, retry up to 3 times | | `userErrors` non-empty | Invalid HTML / field length | Log message, skip product, continue | | No facts to enrich from | Sparse product data | Skip; recommend running `shopify-admin-agentic-
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