By name: linkfox-ehunt-etsy-product-query
description: 通过 EHunt MCP 工具 _ehunt_productQuery（展示名「Etsy商品查询」）按多维度筛选 Etsy 商品（关键词/URL、价格、销量、收藏、评论、上架时间、类目、手工/复古等类型、Pick/Bestsell/Raving 等）。当用户提到 EHunt Etsy 商品、Etsy listing、Etsy 选品、Etsy 爆款、Etsy handmade、Etsy vintage、ehunt items、Etsy商品查询、_ehunt_productQuery 时触发。即使用户未写 EHunt，只要在 Etsy 上搜商品、看销量/价格/标签或筛品，也应触发此技能。
EHunt Etsy 商品查询（_ehunt_productQuery）
在具备 LinkFox「第三方数据服务」MCP 时，按工具名 _ehunt_productQuery 调用（MCP 展示名：Etsy商品查询，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：与店铺接口相同思路，
begin*/end*成对。 - 排序：
sortBy为 1~6（EHunt 上游sort_by）。sortDesc：1=降序，2=升序（与_ehunt_storeQuery的 1/0 不同）。 - 商品类型
productType：1手工、2复古、3数字、4定制、9其他，多选用逗号。 - 货币：
currencyCode默认USD。 - 类目 id：
category为单品类 ID；可先通过类目检索类技能拿到 id。
脚本（可选）
命令行调试：python scripts/ehunt_etsy_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_etsy_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.