linkfox-ehunt-etsy-product-query
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。
How do I install this agent skill?
npx skills add https://github.com/linkfox-ai/linkfox-skills --skill linkfox-ehunt-etsy-product-queryIs this agent skill safe to install?
- Gen Agent Trust Hubpass
This skill provides a mechanism to query Etsy product information, such as sales, prices, and categories, using the EHunt service. It includes a Python script that facilitates interaction with the vendor's API gateway. The skill's behavior is consistent with its stated purpose, and no security risks were identified during the analysis.
- Socketwarn
1 alert: gptAnomaly
- Snykwarn
Risk: MEDIUM · 1 issue
What does this agent skill do?
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。
<!-- LF_LARGE_RESPONSE_BLOCK -->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.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/linkfox-ai/linkfox-skills/linkfox-ehunt-etsy-product-query">View linkfox-ehunt-etsy-product-query on skillZs</a>