EHunt Shopify 店铺查询（ehunt/shopify/storeQuery）

在具备 LinkFox「第三方数据服务」MCP 时，对应网关路由 ehunt/shopify/storeQuery 调用（MCP 展示名：Shopify 店铺查询，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。
• 区间入参：*Min / *Max 成对出现（产品数、广告数、月访问量、月订单量），组成上游区间。
• 店铺年限 year：1=最近 1 年、2=1~2 年、3=2~3 年、4=3 年以上。
• 排序：sortBy 整数枚举（0=产品数,1=类目数,2=月访问量,3=FB 粉丝,4=Ins 粉丝,5=广告数,6=相关度,7=月订单数默认）；orderBy 为 desc（默认）/asc。
• 国家：country 传国家代码（如 US、CN）。

脚本（可选）

命令行调试：python scripts/ehunt_shopify_store_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。

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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_store_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.

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