name: linkfox-ehunt-temu-category-search
description: 通过 EHunt Temu 品类检索(网关路由 ehunt/temu/temuCategorySearch)在已同步到本地库的 EHunt Temu 类目数据中按关键词检索类目中文名、英文名与类目 id,用于商品/店铺筛选的类目 id。当用户提到 EHunt Temu 类目、Temu category id、Temu 类目树、Temu 后台类目、temu 品类、syncTemuCategory(Temu 品类同步)后查类目、Temu category search 时触发。即使用户未写 EHunt,只要在本地已同步的 Temu 类目库里按关键词找类目 id,也应触发此技能。
EHunt Temu 类目检索(ehunt/temu/temuCategorySearch)
在具备 LinkFox「第三方数据服务」MCP 时,对应网关路由 ehunt/temu/temuCategorySearch 调用(MCP 展示名:Temu 品类查询,确切工具名以当前环境下发的工具元数据为准)。数据来自 本地库检索。
前置条件
库内须已有 ehunt/temu/syncTemuCategory(MCP 展示名:Temu 品类同步)写入的全量类目。若无数据或结果为空,应先完成同步再检索。
要点
- 必填:
keyword(子串匹配类目中文名、英文名、类目 id)。 - 分页:
page从 1 起;pageSize默认 50、最大 200。 - 返回的
id/categoryId可作为 Temu 商品查询的categoryHome/categoryBackend、店铺查询的category等入参的类目标识(与具体工具 schema 一致即可)。
脚本(可选)
命令行调试:python scripts/ehunt_temu_category_search.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_category_search.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.