菜单
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.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/40RTY-ai/shopify-admin-skills --skill shopify-admin-agentic-description-enrichment命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
Master skill collection for Shopify store operators. Provides access to all merchandising, marketing, support, and operations capabilities.
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.
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.
| 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"] |
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.
shopify auth login --store <domain>)read_products, write_productsAll 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") |
⚠️ Step 3 (
productUpdate) replacesdescriptionHtmlon live products. This is content the merchant may have hand-written. Always rundry_run: true, export the before/after, and have a human approve the rewrites before committing. Default only touches products undermin_chars.
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.
# 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 }
}
}
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
}
}
human: count enriched + a before/after CSV (product, old_len, new_len, new_description). json: { products_enriched, products_skipped, errors, output_file }.
| 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 |
shopify-admin-agentic-metafields-setup: structured metafields make the descriptions both richer and machine-filterable.