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Linkfox Ehunt Temu Product Query

  • 89 installs
  • 64 repo stars
  • Updated August 3, 2026
  • linkfox-ai/linkfox-skills

Helps with ai & agent building tasks.

About

linkfox-ehunt-temu-product-query is a Claude Code skill in the AI & Agent Building category.

  • linkfox-ehunt-temu-product-query
  • AI & Agent Building
  • AI-coding skill

Linkfox Ehunt Temu Product Query by the numbers

  • 89 all-time installs (skills.sh)
  • Ranked #4,882 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/linkfox-ai/linkfox-skills --skill linkfox-ehunt-temu-product-query

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Listed on Skillselion
Installs89
repo stars64
Last updatedAugust 3, 2026
Repositorylinkfox-ai/linkfox-skills

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

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-0order_total-0rating-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

<!-- 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_temu_product_query.py --out-dir <DIR> '<params>'
python scripts/response_io.py read <file> --fields "<paths>"   # or --path "<JMESPath>"
Pick --out-dir outside 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. <!-- /LF_LARGE_RESPONSE_BLOCK -->

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