linkfox-mpstats-ozon-product-detail

name: linkfox-mpstats-ozon-product-detail description: MPSTATS Ozon 俄罗斯站 SKU 全量详情批量查询。一次最多传 100 个 Ozon 商品 ID，返回每个 SKU 的价格、折扣、Ozon Card 价、评分、评论数、库存、销量、销售额、潜在销售额/损失销售额、上架日期、图片等完整商品卡。当用户提到 Ozon 商品详情、Ozon SKU 详情、Ozon 价格/评分/销量/库存核对、批量 Ozon SKU 查询、竞品 Ozon 基础数据拉取、Ozon 竞品卡片、MPSTATS Ozon detail, Ozon SKU detail, Ozon product card, Ozon batch lookup, Russian marketplace product detail 时触发此技能。即使用户未明确说"MPSTATS"，只要意图是按 Ozon SKU 拉取全量商品卡数据，也应触发此技能。

MPSTATS Ozon Product Detail (Batch)

This skill batch-fetches the full product card for one or more Ozon (Russia) SKUs via MPSTATS. Returned fields include price, Ozon Card price, discount, rating, reviews, stock, monthly sales units, monthly sales revenue, lost profit, potential revenue, first listing date, image, and more.

Core Concepts

Batch semantics: Pass up to 100 productIds in a single call. The server fans out concurrently and automatically retries each failed SKU once; partial success is allowed, so a mixed list is normal.

Fulfillment model per SKU: Each product card carries deliveryScheme:

• FBO — Fulfillment by Ozon (stock in Ozon warehouses)
• FBS — Fulfillment by Seller (seller-shipped)

Pass includeFbs: true to allow FBS SKUs and FBS-scoped metrics into the response; false (or omitted) keeps the result FBO-centric. This switch applies to the whole batch.

Previous-period comparison: The card includes previousSalesUnits / previousRevenue — sales and revenue from the equal-length period immediately before [startDate, endDate] — ready for MoM / period-over-period diffs without extra calls.

Revenue potential: revenuePotential projects what the SKU could have earned if it had been in stock every day of the window; compare with monthlySalesRevenue to quantify stock-out drag, together with lostProfit / lostProfitPercent.

Date window: startDate / endDate define the period for all period-aggregated metrics. Latest selectable date is yesterday (T-1); today and future dates are rejected.

Parameters

API Usage

This tool calls the LinkFox tool gateway API. See references/api.md for calling conventions, request parameters, response structure, and error codes. You can also execute scripts/mpstats_ozon_product_detail.py directly for ad-hoc queries.

Usage Examples

1. Single-SKU detail

{"productIds": [1786874757]}

2. Batch lookup with period

{
  "productIds": [1786874757, 151623766, 142257239],
  "startDate": "2025-03-01",
  "endDate": "2025-03-31",
  "includeFbs": true
}

3. FBO-only snapshot

{"productIds": [1786874757, 151623766], "includeFbs": false}

4. SKUs discovered upstream — full card

{"productIds": [<list from mpstats-ozon-product-search>]}

How to Chain with Other Ozon Skills

1. Search → detail: Use mpstats-ozon-product-search to resolve a keyword / brand / seller into productIds, then pass them here for full metrics.
2. Detail vs trend: This endpoint is a period aggregate per SKU; for day-by-day time-series on a single SKU, use mpstats-ozon-product-trend.
3. Detail vs drill-downs: When the input dimension is a brand / category / seller (not a SKU list), prefer brand-products / category-products / seller-products — they already return aggregated metrics per SKU under that dimension.

Display Rules

1. Compact table — lead with productId, title, price, monthlySalesUnits, monthlySalesRevenue, rating, reviewCount, balance, deliveryScheme, firstDate. Pull revenuePotential / lostProfit / lostProfitPercent in when the user asks about stock-out impact.
2. Currency — Ozon native currency is RUB; the currency field carries the symbol. Do not silently relabel.
3. Partial success — the response carries successCount / failedCount / failures; when failedCount > 0, list the failed productIds from failures to the user rather than silently dropping them.
4. Period-over-period — when both current and previous* fields are present, render them side-by-side or as diff; don't report a single-period number as "trend".
5. With-stock vs all-days — salesPerDayWithStock / dailySalesRevenueWithStock only count days that had inventory; distinguish from the plain salesPerDay / dailySalesRevenue.
6. Delivery model — prefer the per-SKU deliveryScheme value over assuming FBO; remind users when a batch mixes FBO and FBS.
7. No business advice — present data; do not extrapolate "this SKU is worth selling" without a wider analysis.

Important Limitations

• 100-SKU batch cap — split larger input lists and call multiple times; the Agent must paginate.
• Ozon-only — this tool does not cover Wildberries or other Russian marketplaces.
• T-1 data — endDate must not be today or future.
• FBS coverage — some categories have partial FBS coverage; if the input set is FBS-heavy, expect sparser cards.
• Field set differs from brand/seller — this endpoint does not return brandId, country, category, minPrice / maxPrice / averagePrice, balanceFbs, frozenStocks, warehousesCount, daysInSite / daysInStock / turnoverDays, position / categoryPosition / revenueSharePercent, isFbs. Use brand-products / category-products / seller-products if those are needed.
• No translation — titles are returned in Russian; translate on demand when presenting to Chinese / English users.

User Expression & Scenario Quick Reference

Applicable — Per-SKU Ozon card lookup:

Not applicable — Needs beyond per-SKU card:

• Keyword-based discovery → use mpstats-ozon-product-search
• Day-by-day time-series for one SKU → use mpstats-ozon-product-trend
• Listing copy / reviews / images analysis beyond URL → out of scope
• Brand / category / seller drill-down with filters → use the matching drill-down skill

Boundary judgment: If the user already has a SKU list and wants per-SKU sales / price / stock / rating, this is the skill. If they don't yet have SKUs, route through the search or drill-down skills first.

Feedback:

Auto-detect and report feedback via the Feedback API when any of the following apply:

1. The functionality or purpose described in this skill does not match actual behavior
2. The skill's results do not match the user's intent
3. The user expresses dissatisfaction or praise about this skill
4. Anything you believe could be improved

Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.

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/mpstats_ozon_product_detail.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.

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