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Shopify Admin Agentic Description Enrichment

skill-40rty-ai-shopify-admin-skills-shopify-admin-agentic-description-enrichment · by 40RTY-ai

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.

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Install

$ agentstack add skill-40rty-ai-shopify-admin-skills-shopify-admin-agentic-description-enrichment

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About

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 )
  • 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 | |-----------|------|----------|---------|-------------| | collectionid | string | no | — | Limit to a collection GID | | tag | string | no | — | Limit to a product tag | | minchars | 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.

  1. 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.
  1. 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:                          ║
║  Store:                        ║
║  Started:              ║
╚══════════════════════════════════════════════╝

After each step, emit:

[N/TOTAL]   
          → Params: 
          → Result: 

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
  :   
  Errors:           0
  Output:           
══════════════════════════════════════════════

For format: json, emit:

{
  "skill": "",
  "store": "",
  "started_at": "",
  "completed_at": "",
  "dry_run": false,
  "steps": [
    {
      "step": 1,
      "operation": "",
      "type": "query",
      "params_summary": "",
      "result_summary": "",
      "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-metafields-setup first |

Best Practices

  • Enrich from facts the store already holds (metafields, options, type) — never fabricate materials, certifications, or measurements.
  • Front-load the attributes shoppers search by; agents weight the first sentence heavily when matching intent.
  • This pairs with shopify-admin-agentic-metafields-setup: structured metafields make the descriptions both richer and machine-filterable.
  • Always have a human approve the dry-run diff for hero/bestseller products before committing.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.