linkfox-ehunt-etsy-store-query
通过 EHunt MCP 工具 `_ehunt_storeQuery`(展示名「Etsy店铺查询」)按多维度筛选 Etsy 店铺(销量、收藏、评论、开店时间、国家、主营类目、Raving/星标等)。当用户提到 EHunt Etsy 店铺、Etsy 店搜、Etsy seller、Etsy 店铺排行、Etsy 周销量店铺、ehunt stores、Etsy店铺查询、_ehunt_storeQuery 时触发。即使用户未写 EHunt,只要在 Etsy 上找店铺、筛店铺数据或分析店铺表现,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-store-queryIs this agent skill safe to install?
- Gen Agent Trust Hubpass
No security issues detected. The skill is designed to query Etsy store information via the vendor's API gateway and follows security best practices for credential management.
- Socketpass
No alerts
- Snykwarn
Risk: MEDIUM · 1 issue
What does this agent skill do?
EHunt Etsy 店铺查询(_ehunt_storeQuery)
在具备 LinkFox「第三方数据服务」MCP 时,按工具名 _ehunt_storeQuery 调用(MCP 展示名:Etsy店铺查询,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。 - 区间入参:
begin*/end*成对对应上游逗号范围;只填一侧时上游为「起始~」或「~结束」。 - 排序:
sortBy仅 8~11(8 总销量、9 周销量、10 评论数、11 收藏数)。sortDesc:1=降序,0=升序(勿与商品接口的sortDesc混用)。
脚本(可选)
命令行调试:python scripts/ehunt_etsy_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。
<!-- 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_store_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-store-query">View linkfox-ehunt-etsy-store-query on skillZs</a>