SuperAPI AI Directory

linkfox-ehunt-temu-store-query

Data & analytics

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Updated 10-16 06:23

About this skill

EHunt Temu store query (ehunt/temu/storeQuery)

When the LinkFox "Third-Party Data Service" MCP is available, the corresponding gateway route ehunt/temu/storeQuery is called (MCP display name:Temu store query, the exact tool name is subject to the tool metadata issued in the current environment). Authentication and upstream routing are handled by the gateway; if the response contains a root-level code field, whether it is successful is subject to the live network.

Key points

  • Pagination:page starts from 1;pageSize defaults to 20, maximum 100.
  • Range parameters:*Min / *Max appear in pairs (total/weekly/monthly sales volume, total/weekly/monthly sales amount, rating, reviews, followers, product count), forming the upstream range.
  • Site:siteId country site ID, multiple separated by commas (e.g. 211=United States,76=United Kingdom).
  • Category:category backend category ID, multiple separated by commas.
  • Managed mode:isLocal(0=fully managed, 1=semi managed, string).
  • Store opening time:listedTimeBegin / listedTimeEnd(YYYY-MM-DD)。
  • Sort:sortBy is a "field-direction" string, e.g. order_week_count-0(weekly sales volume descending, default),order_count-0、total_revenue-0、rating-0。

Script (optional)

Command-line debugging:python scripts/ehunt_temu_store_query.py '<JSON>'(requires LINKFOXAGENT_API_KEY). See the end of references/api.md .

Reference

For the input/output parameter table, see 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_store_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.