name: linkfox-ehunt-temu-product-query
description: 通过 EHunt Temu 商品查询(网关路由 ehunt/temu/productQuery)按多维度筛选 Temu 商品(关键词/商品 ID/店铺 ID、前后台类目、价格、评分、评论、总/周/日销量、上架时间、全托管/半托管、半托管地区、标签等)。当用户提到 EHunt Temu 商品、Temu 选品、拼多多跨境、Temu 爆款、Temu 半托管、全托管商品、Temu product query、temu items 时触发。即使用户未写 EHunt,只要在 Temu 上搜商品、看销量/评分/价格或筛品,也应触发此技能。
EHunt Temu 商品查询(ehunt/temu/productQuery)
在具备 LinkFox「第三方数据服务」MCP 时,对应网关路由 ehunt/temu/productQuery 调用(MCP 展示名:Temu 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:
*Begin/*End成对出现(价格、评分、评论、总/周/日销量、上架时间),组成上游区间。 - 类目:
categoryHome前台类目 ID、categoryBackend后台类目 ID;可先用 Temu 品类检索拿到 id。 - 托管模式:
isLocal(0=全托管,1=半托管);半托管可用region限定地区(多个逗号分隔)。 - 上下架:
soldOut(0=上架,1=下架)。 - 标签:
tags/customTags多个用逗号分隔。 - 排序:
sortBy为「字段-方向」字符串,如order_week-0(周销量降序,默认)、price-0、order_total-0、rating-0。
脚本(可选)
命令行调试:python scripts/ehunt_temu_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_temu_product_query.py --out-dir <DIR> '<params>'
python scripts/response_io.py read <file> --fields "<paths>" # or --path "<JMESPath>"
Pick
--out-diroutside 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.