ClawHub

Ehunt Temu Store Query

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通过 EHunt Temu 店铺查询（网关路由 `ehunt/temu/storeQuery`）按多维度筛选 Temu 店铺（店名/ID、国家站点、后台类目、全托管/半托管、总/周/月销量与销售额、评分、评论、粉丝、商品数、开店时间等）。当用户提到 EHunt Temu 店铺、Temu 店铺分析、Temu seller、Temu 店铺排行、Temu 半托管店铺、Temu 销售额、temu stores、Temu store query 时触发。即使用户未写 EHunt，只要在 Temu 上找店铺、筛店铺数据或分析店铺表现，也应触发此技能。

Install

openclaw skills install linkfox-ehunt-temu-store-query

EHunt Temu 店铺查询（ehunt/temu/storeQuery）

在具备 LinkFox「第三方数据服务」MCP 时，对应网关路由 ehunt/temu/storeQuery 调用（MCP 展示名：Temu 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（总/周/月销量、总/周/月销售额、评分、评论、粉丝、商品数），组成上游区间。
  • 站点：siteId 国家站点 ID，多个逗号分隔（如 211=美国、76=英国）。
  • 类目：category 后台类目 ID，多个逗号分隔。
  • 托管模式：isLocal（0=全托管，1=半托管，字符串）。
  • 开店时间：listedTimeBegin / listedTimeEnd（YYYY-MM-DD）。
  • 排序：sortBy 为「字段-方向」字符串，如 order_week_count-0（周销量降序，默认）、order_count-0、total_revenue-0、rating-0。

脚本（可选）

命令行调试：python scripts/ehunt_temu_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_temu_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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