shopify-admin-agentic-description-enrichment: Reusable for AI Agents | OpenAgentSkill

Overview

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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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

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.
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.
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-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.

View source ↗

File metadata

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

View original text

---
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

```graphql
# 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 }
  }
}
```

```graphql
# 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:
```json
{
  "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-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.

Review the source

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

Permission surface may require sandboxing
Financial research output is not financial advice; require human review before any live investment decision
Financial research output is not financial advice; require human review before any live investment decision.
Quality score needs review

Open full audit

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Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
3Check the output and changed files. Report only what actually ran; keep the source revision for reproduction.

Check the source for dependencies, API keys and third-party costs. A public repository does not mean every service is free.

Source & trust

Indexed

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

License: MIT
Version: 1.0.0
Last GitHub push: Aug 14, 2026
Registry updated: Sep 4, 2026
Instruction path: skills/agentic/shopify-admin-agentic-description-enrichment/SKILL.md @ 6765cb4f436b

Version reported in registry metadata; check source releases before relying on it.

Quality

69/100

Promising

Trust

66/100

Sandbox only

Audit

79/100

Needs review

Agent access

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

Open install API LLM text format Open manifest Auto-resolve Plan

More details

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      {
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      "install": "npx skills add 40RTY-ai/shopify-admin-skills --skill shopify-admin-agentic-description-enrichment",
      "installSafety": "standard package or runtime install path",
      "permissionSurface": "shell or command execution, filesystem or document access",
      "documentation": "Usable metadata, review docs",
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      "Permission surface: shell or command execution, filesystem or document access"
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      "Quality score needs review",
      "Permission surface needs review: shell or command execution, filesystem or document access",
      "Stars/forks activity: 182 stars, 18 forks; issue activity unavailable in current metadata",
      "Permission surface: shell or command execution, filesystem or document access"
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    "Permission surface may require sandboxing",
    "Financial research output is not financial advice; require human review before any live investment decision",
    "Financial research output is not financial advice; require human review before any live investment decision.",
    "Quality score needs review"
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  "agent_contract": {
    "task_input": "Use shopify-admin-agentic-description-enrichment in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
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      "Audit: 79/100 Needs review",
      "Safety: 35/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
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      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
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  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "40rty-ai-shopify-admin-agentic-description-enrichment",
      "task": "Use shopify-admin-agentic-description-enrichment in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/40rty-ai-shopify-admin-agentic-description-enrichment",
    "api": "https://www.openagentskill.com/api/agent/skills/40rty-ai-shopify-admin-agentic-description-enrichment",
    "audit": "https://www.openagentskill.com/skills/40rty-ai-shopify-admin-agentic-description-enrichment/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=40rty-ai-shopify-admin-agentic-description-enrichment&task=Use%20shopify-admin-agentic-description-enrichment%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20shopify-admin-agentic-description-enrichment%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20shopify-admin-agentic-description-enrichment%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/40rty-ai-shopify-admin-agentic-description-enrichment/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/40rty-ai-shopify-admin-agentic-description-enrichment"
  }
}

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Creator: 40RTY-ai
Source: 40RTY-ai/shopify-admin-skills
Indexed by: OpenAgentSkill community index

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