| name | linkfox-ehunt-shopify-product-query |
| version | 1.0.0 |
| category | product-sourcing |
| description | 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。 |
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.
