linkfox-ehunt-shopify-product-query

Original：🇺🇸 English

Translated

2 scriptsChecked / no sensitive code detected

通过 EHunt Shopify 商品查询（网关路由 `ehunt/shopify/productQuery`）按多维度筛选独立站 Shopify 商品（关键词/URL、价格、周销量、上架时间、Facebook 广告、竞争度、是否有货源、发货国家等）。当用户提到 EHunt Shopify 商品、Shopify 选品、独立站选品、Shopify 爆款、Shopify dropshipping、独立站铺货、Facebook 广告商品、Shopify product query、shopify items 时触发。即使用户未写 EHunt，只要在 Shopify 独立站上搜商品、看周销量/销售额/竞争度或筛品，也应触发此技能。

23installs

Sourcelinkfox-ai/linkfox-skills

Added on2026-07-04

NPX Install

npx skill4agent add linkfox-ai/linkfox-skills linkfox-ehunt-shopify-product-query

SKILL.md Content

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EHunt Shopify 商品查询（

ehunt/shopify/productQuery

）

在具备 LinkFox「第三方数据服务」MCP 时，对应网关路由 ehunt/shopify/productQuery
调用（MCP 展示名：Shopify 商品查询，确切工具名以当前环境下发的工具元数据为准）。鉴权与上游路由由网关处理；若响应含根级

code

字段，是否成功以实网为准。

要点

分页：
```
page
```
从 1 起；
```
pageSize
```
默认 20、最大 100（建议 ≤50）。
区间入参：
```
*Min
```
/
```
*Max
```
成对出现，组成上游区间；只填一侧时上游为「起始~」或「~结束」。
排序：
```
sortBy
```
为整数枚举（默认
```
14
```
=周销量降序，另含价格/广告数/竞争度/销售额等多种取值，详见
```
references/api.md
```
）。
布尔类筛选：
```
facebookAd
```
（1=有广告）、
```
hasSupplier
```
（1=有货源，0=无）、
```
showDeleted
```
（1=含已下架）均为整数开关。
发货国家：
```
country
```
传两位国家代码（如
```
US
```
）。

脚本（可选）

命令行调试：

python scripts/ehunt_shopify_product_query.py '<JSON>'

（需

LINKFOXAGENT_API_KEY

）。详见 references/api.md 末尾。

参考

入参/出参表见 references/api.md。

Handling Large Responses

To avoid overflowing the agent context, persist the response to disk and extract only the fields you need:

python scripts/response_io.py run --script scripts/ehunt_shopify_product_query.py --out-dir <DIR> '<params>'
python scripts/response_io.py read <file> --fields "<paths>"   # or --path "<JMESPath>"

Pick
--out-dir
outside any git working tree (e.g.
/tmp/...
on Unix,
%TEMP%/...
on Windows). Persisted responses may contain PII, pricing, or auth-sensitive data — do not commit them. Files are not auto-deleted; clean up when the task is done.

run

writes the full response to a file and emits only a schema preview + file path.

read

projects specific fields, with

--limit/--offset

for slicing and

--format json|jsonl|csv|table

for output.

When to prefer this pattern — apply your judgment based on the response characteristics, e.g.:

High field count per record, or fields you don't need
Batch/paginated results (multiple items per call)
Long-text fields (descriptions, reviews, HTML, time series)
Output reused across later steps rather than consumed immediately

For small, single-use responses, calling the main script directly is fine.

⚠️ The preview is a truncated schema + sample, not the full data. Any field-level decision must read from the persisted file via

read

.

linkfox-ehunt-shopify-product-query

NPX Install

Tags

SKILL.md Content

EHunt Shopify 商品查询（
`ehunt/shopify/productQuery`
）

要点

脚本（可选）

参考

Handling Large Responses

linkfox-ehunt-shopify-product-query

NPX Install

Tags

SKILL.md Content

EHunt Shopify 商品查询（ehunt/shopify/productQuery）

要点

脚本（可选）

参考

Handling Large Responses

EHunt Shopify 商品查询（
`ehunt/shopify/productQuery`
）