| name | ecommerce.temu-store-query |
| version | 1.0.0 |
| category | product-sourcing |
| description | Query Temu stores/sellers via EHunt filters. Triggers: Temu store analysis, Temu seller, store ranking, revenue, followers, semi-managed stores. Use for seller/store-level analysis, not individual product sourcing; use temu-product-query for products.
|
EHunt Temu Store Query (ehunt/temu/storeQuery)
Core Question
Which Temu stores match the user's seller, revenue, category, region, or performance filters?
When to Use
- User asks to find or rank Temu stores/sellers.
- User wants to compare Temu seller performance, revenue, followers, ratings, product count, or category focus.
- User asks for semi-managed or fully managed Temu stores in specific regions.
- User wants store-level sourcing leads rather than individual product listings.
Clarify or Infer Before Querying
If the user request is broad or ambiguous, identify:
- target site or region
- category or seller niche
- performance metric to sort by, such as weekly sales, total revenue, rating, followers, or product count
- fulfillment mode if relevant
- desired result count and time window
Use sensible defaults when the user's intent is clear: US site, weekly sales descending, first page, 20 stores.
Differs From / Not Applicable
- Use
ecommerce.temu-product-query when the user wants individual Temu products, product prices, product sales, ratings, tags, or product sourcing.
- Use this skill when the unit of analysis is the seller/store.
- Do not use for TikTok Shop data, Amazon seller data, product detail pages, or listing copy optimization.
Workflow
- Understand the store-level goal and normalize filters.
- Resolve region/site, category, fulfillment mode, ranges, and sort order.
- Query EHunt Temu store data.
- Return a compact seller table with the most relevant metrics.
- Add a short interpretation: strongest stores, unusual outliers, and next filters to try.
Output Structure
Default output should include:
- Query assumptions and filters used
- Store ranking table: store name/ID, site, category focus, sales, revenue, rating, followers, product count, fulfillment mode
- Key observations: top performers, fast-growing or high-efficiency stores, weak data points
- Suggested next step: refine category, inspect products from selected stores, or compare regions
Calls the EHunt data source via the Nexscope proxy gateway, route /api/v1/tools/research/ehunt/temu/storeQuery (display name: Temu Store Query). Authentication and routing are handled by the Nexscope proxy; if the response contains a root-level code field, success is determined by the live response.
Key Points
- Pagination:
page starts at 1; pageSize defaults to 20, max 100.
- Range parameters:
*Min / *Max pairs (total/weekly/monthly sales, total/weekly/monthly revenue, rating, reviews, followers, product count) form upstream range filters.
- Site:
siteId country site ID, comma-separated for multiple values (100 = US, 101 = UK, 102 = EU, 103 = JP, 105 = KR).
- Category:
category back-end category ID, comma-separated for multiple values.
- Fulfillment mode:
isLocal (0 = fully managed, 1 = semi-managed, string type).
- Opening date:
listedTimeBegin / listedTimeEnd (YYYY-MM-DD).
- Sorting:
sortBy is a "field-direction" string, e.g. order_week_count-0 (weekly sales descending, default), order_count-0, total_revenue-0, rating-0.
Scripts (Optional)
CLI debugging: python scripts/ehunt_temu_store_query.py '<JSON>' (requires environment variables NEXSCOPE_API_KEY and NEXSCOPE_PROXY_BASE). See references/api.md for details.
Reference
Full request/response parameter tables: 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 do not 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.
Warning: The preview is a truncated schema + sample, not the full data. Any field-level decision must read from the persisted file via read.
Environment Variables
| Variable | Required | Description |
|---|
NEXSCOPE_PROXY_BASE | Yes | NexScope proxy base URL |
NEXSCOPE_API_KEY | Yes | NexScope proxy API key |
