shopify-admin-agentic-product-taxonomy: Workflow Automation for AI... | OpenAgentSkill

Overview

Assign every product a Shopify Standard Product Taxonomy category so AI agents can map a shopper's intent to the right category and surface the store's products.

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Purpose

AI shopping agents resolve a query ("running shoes", "office chair", "sustainable sneakers") to a taxonomy node, then retrieve products in that node. Products with no Standard Product Taxonomy category are invisible to that mapping — they only surface on exact keyword luck. This skill finds uncategorized (or mis-categorized) products and assigns the correct Shopify standard taxonomy category, inferred from title/type/tags and confirmed against the live taxonomy tree. Fixes category-taxonomy-api and lifts catalog-intent-alignment.

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
only_missing	bool	no	true	If true, only assign products with no category; if false, also review mismatches
confidence_floor	float	no	0.7	Skip products whose best taxonomy match scores below this

Safety

⚠️ Step 4 (productUpdate) sets the category on live products, which affects storefront facets, marketplaces, and tax. A wrong category mis-files a product everywhere. Run dry_run: true, review the proposed product → category mapping, and only auto-assign matches above confidence_floor; queue the rest for human review.

Workflow Steps

OPERATION: products — query Inputs: first: 250, optional filter; fields title, productType, tags, category{ id fullName }; paginate. Expected output: Products with their current category (or null).
OPERATION: taxonomy — query Inputs: search the standard taxonomy tree by candidate terms derived from each product's type/title. Expected output: Candidate taxonomy category nodes (id + fullName) to match against.
COMPUTE (no API): score each product against candidate nodes; pick the best ≥ confidence_floor. Emit the proposed mapping.
OPERATION: productUpdate — mutation Inputs: { id, category: <taxonomyCategoryId> } per confident match. Expected output: Updated product category; collect userErrors.

GraphQL Operations

# products:query — validated against api_version 2025-01
query TaxonomyProducts($first: Int!, $after: String, $query: String) {
  products(first: $first, after: $after, query: $query) {
    edges {
      node {
        id
        title
        productType
        tags
        category { id fullName }
      }
    }
    pageInfo { hasNextPage endCursor }
  }
}

# taxonomy:query — validated against api_version 2025-01
query TaxonomySearch($search: String) {
  taxonomy {
    categories(first: 20, search: $search) {
      edges { node { id fullName isLeaf level } }
    }
  }
}

# productUpdate:mutation — validated against api_version 2025-01
mutation TaxonomyAssign($input: ProductInput!) {
  productUpdate(input: $input) {
    product { id category { id fullName } }
    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 categorized + a CSV (product, old_category, new_category, confidence) and a "needs review" list below the floor. json: { categorized, needs_review, errors, output_file }.

Error Handling

Error	Cause	Recovery
`THROTTLED`	API rate limit	Wait 2s, retry up to 3 times
No taxonomy match	Niche/ambiguous product	Add to needs-review list, do not guess
`userErrors` on update	Invalid category id	Log, skip, continue

Best Practices

Pick the most specific (leaf) node you're confident in — agents match deeper categories more precisely than top-level ones.
Keep only_missing: true for the first pass; re-categorizing existing assignments is higher-risk and best reviewed.
Aligning the category with your storefront collections compounds the benefit: agents and on-site filters then agree.
Re-run shopify-admin-agentic-readiness-audit to confirm the Matchable pillar improved.

View source ↗

File metadata

name: shopify-admin-agentic-product-taxonomy
role: agentic
description: "Assign every product a Shopify Standard Product Taxonomy category so AI agents can map a shopper's intent to the right category and surface the store's products."
toolkit: shopify-admin, shopify-admin-execution
api_version: "2025-01"
graphql_operations:
  - products:query
  - taxonomy:query
  - productUpdate:mutation
status: stable
compatibility: Claude Code, Cursor, Codex, Gemini CLI
audit_signals:
  - category-taxonomy-api
  - catalog-intent-alignment

View original text

---
name: shopify-admin-agentic-product-taxonomy
role: agentic
description: "Assign every product a Shopify Standard Product Taxonomy category so AI agents can map a shopper's intent to the right category and surface the store's products."
toolkit: shopify-admin, shopify-admin-execution
api_version: "2025-01"
graphql_operations:
  - products:query
  - taxonomy:query
  - productUpdate:mutation
status: stable
compatibility: Claude Code, Cursor, Codex, Gemini CLI
audit_signals:
  - category-taxonomy-api
  - catalog-intent-alignment
---

## Purpose
AI shopping agents resolve a query ("running shoes", "office chair", "sustainable sneakers") to a taxonomy node, then retrieve products in that node. Products with no Standard Product Taxonomy category are invisible to that mapping — they only surface on exact keyword luck. This skill finds uncategorized (or mis-categorized) products and assigns the correct Shopify standard taxonomy category, inferred from title/type/tags and confirmed against the live taxonomy tree. Fixes `category-taxonomy-api` and lifts `catalog-intent-alignment`.

## 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 |
| only_missing | bool | no | true | If true, only assign products with no category; if false, also review mismatches |
| confidence_floor | float | no | 0.7 | Skip products whose best taxonomy match scores below this |

## Safety

> ⚠️ Step 4 (`productUpdate`) sets the `category` on live products, which affects storefront facets, marketplaces, and tax. A wrong category mis-files a product everywhere. Run `dry_run: true`, review the proposed `product → category` mapping, and only auto-assign matches above `confidence_floor`; queue the rest for human review.

## Workflow Steps

1. **OPERATION:** `products` — query
   **Inputs:** `first: 250`, optional filter; fields `title`, `productType`, `tags`, `category{ id fullName }`; paginate.
   **Expected output:** Products with their current category (or null).

2. **OPERATION:** `taxonomy` — query
   **Inputs:** search the standard taxonomy tree by candidate terms derived from each product's type/title.
   **Expected output:** Candidate taxonomy category nodes (id + fullName) to match against.

3. **COMPUTE (no API):** score each product against candidate nodes; pick the best ≥ `confidence_floor`. Emit the proposed mapping.

4. **OPERATION:** `productUpdate` — mutation
   **Inputs:** `{ id, category: <taxonomyCategoryId> }` per confident match.
   **Expected output:** Updated product category; collect `userErrors`.

## GraphQL Operations

```graphql
# products:query — validated against api_version 2025-01
query TaxonomyProducts($first: Int!, $after: String, $query: String) {
  products(first: $first, after: $after, query: $query) {
    edges {
      node {
        id
        title
        productType
        tags
        category { id fullName }
      }
    }
    pageInfo { hasNextPage endCursor }
  }
}
```

```graphql
# taxonomy:query — validated against api_version 2025-01
query TaxonomySearch($search: String) {
  taxonomy {
    categories(first: 20, search: $search) {
      edges { node { id fullName isLeaf level } }
    }
  }
}
```

```graphql
# productUpdate:mutation — validated against api_version 2025-01
mutation TaxonomyAssign($input: ProductInput!) {
  productUpdate(input: $input) {
    product { id category { id fullName } }
    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 categorized + a CSV (`product, old_category, new_category, confidence`) and a "needs review" list below the floor. `json`: `{ categorized, needs_review, errors, output_file }`.

## Error Handling
| Error | Cause | Recovery |
|-------|-------|----------|
| `THROTTLED` | API rate limit | Wait 2s, retry up to 3 times |
| No taxonomy match | Niche/ambiguous product | Add to needs-review list, do not guess |
| `userErrors` on update | Invalid category id | Log, skip, continue |

## Best Practices
- Pick the most specific (leaf) node you're confident in — agents match deeper categories more precisely than top-level ones.
- Keep `only_missing: true` for the first pass; re-categorizing existing assignments is higher-risk and best reviewed.
- Aligning the category with your storefront collections compounds the benefit: agents and on-site filters then agree.
- Re-run `shopify-admin-agentic-readiness-audit` to confirm the Matchable pillar improved.

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

License: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Stars/forks activity: 182 stars, 18 forks; issue activity unavailable in current metadata
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Open full audit

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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 & usage notes

Indexed

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

Source repository: 40RTY-ai/shopify-admin-skills
License: MIT
Version: 1.0.0
Last GitHub push: Aug 14, 2026
Registry updated: Sep 4, 2026
Instruction path: skills/agentic/shopify-admin-agentic-product-taxonomy/SKILL.md @ 6765cb4f436b

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

Quality

66/100

Promising

Trust

62/100

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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      "install_command": "npx skills add 40RTY-ai/shopify-admin-skills --skill shopify-admin-agentic-product-taxonomy",
      "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."
    }
  },
  "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-product-taxonomy",
      "task": "Use shopify-admin-agentic-product-taxonomy 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-product-taxonomy",
    "api": "https://www.openagentskill.com/api/agent/skills/40rty-ai-shopify-admin-agentic-product-taxonomy",
    "audit": "https://www.openagentskill.com/skills/40rty-ai-shopify-admin-agentic-product-taxonomy/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=40rty-ai-shopify-admin-agentic-product-taxonomy&task=Use%20shopify-admin-agentic-product-taxonomy%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20shopify-admin-agentic-product-taxonomy%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20shopify-admin-agentic-product-taxonomy%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/40rty-ai-shopify-admin-agentic-product-taxonomy/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/40rty-ai-shopify-admin-agentic-product-taxonomy"
  }
}

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

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