linkfox-mpstats-ozon-seller-products

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MPSTATS Ozon 俄罗斯站按卖家 ID 下钻商品列表。返回该卖家下全部 SKU 的销量、销售额、价格、评分、库存、周转、损失销售额等完整指标,支持多维数值筛选、排序、货币换算。用于店铺结构分析、卖家爆款拆解、竞争对手店铺对标。当用户提到 Ozon 卖家商品、Ozon 店铺分析、Ozon 卖家下钻、Ozon 卖家 SKU、Ozon 店铺爆款、Ozon 竞争店铺、MPSTATS seller, Ozon seller drill-down, Ozon shop audit, Russian marketplace seller SKUs, Ozon store structure 时触发此技能。即使用户未明确说"MPSTATS",只要意图是按 Ozon 卖家 ID 看该店铺下全部商品的销售表现,也应触发此技能。

linkfox-ai By linkfox-ai schedule Updated 6/12/2026

name: linkfox-mpstats-ozon-seller-products description: MPSTATS Ozon 俄罗斯站按卖家 ID 下钻商品列表。返回该卖家下全部 SKU 的销量、销售额、价格、评分、库存、周转、损失销售额等完整指标,支持多维数值筛选、排序、货币换算。用于店铺结构分析、卖家爆款拆解、竞争对手店铺对标。当用户提到 Ozon 卖家商品、Ozon 店铺分析、Ozon 卖家下钻、Ozon 卖家 SKU、Ozon 店铺爆款、Ozon 竞争店铺、MPSTATS seller, Ozon seller drill-down, Ozon shop audit, Russian marketplace seller SKUs, Ozon store structure 时触发此技能。即使用户未明确说"MPSTATS",只要意图是按 Ozon 卖家 ID 看该店铺下全部商品的销售表现,也应触发此技能。

MPSTATS Ozon Seller Products

This skill drills into all Ozon (Russia) products sold by a given seller, returning per-SKU sales, revenue, price, rating, stock, turnover, lost profit, and more. Designed for store-structure audits, bestseller dissection within a shop, and head-to-head competitor-store comparison.

Core Concepts

Seller ID, not name: sellerId must be a numeric string — the sellerId field Ozon / MPSTATS uses to identify a shop. Do not pass a brand name, category path, or human-readable seller name. If you only have the seller name, resolve the ID via mpstats-ozon-product-search (seller-filtered) and read sellerId from the result.

Filters & ops: Same AND-combined numeric filter model as brand-products and category-products. See Filter Reference.

Currency: Default RUB; override with currency / currencyRate for USD / EUR / CNY views.

FBO / FBS: includeFbs: true folds FBS into the numbers; false keeps FBO-only.

Parameters

Parameter Type Required Description
sellerId string yes Ozon seller ID as numeric string, e.g. "3628678"
startDate string no Stats window start, YYYY-MM-DD; latest = yesterday
endDate string no Stats window end, YYYY-MM-DD; latest = yesterday
page integer no Page number, starts at 1
pageSize integer no Rows per page, 1-100, default 100
sortField string no snake_case column (sales, revenue, ...)
sortDirection string no asc / desc
currency string no Currency code, default RUB
currencyRate integer no Custom rate for non-default currency
includeFbs boolean no Include FBS data
filters array no Numeric filter list

Filter Reference

Each filters entry: {"field": "<snake_case>", "op": "<OP>", "value": <num>, "value2": <num?>}.

Common fields: sales, final_price, rating, comments, balance, revenue, days_in_stock, turnover_days, lost_profit, category_position.

Operators: GTE, LTE, GT, LT, EQ, NOT_EQ, BETWEEN (requires value2).

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_seller_products.py directly for ad-hoc queries.

Usage Examples

1. Seller's top-100 by sales

{
  "sellerId": "3628678",
  "sortField": "sales",
  "sortDirection": "desc",
  "pageSize": 100
}

2. Store's revenue top-20

{
  "sellerId": "3628678",
  "sortField": "revenue",
  "sortDirection": "desc",
  "pageSize": 20
}

3. High-turnover star products

{
  "sellerId": "3628678",
  "filters": [
    {"field": "sales", "op": "GTE", "value": 30},
    {"field": "turnover_days", "op": "LTE", "value": 20}
  ],
  "sortField": "revenue",
  "sortDirection": "desc"
}

4. Stockout pain points for the store

{
  "sellerId": "3628678",
  "filters": [{"field": "lost_profit", "op": "GTE", "value": 100000}],
  "sortField": "lost_profit",
  "sortDirection": "desc"
}

5. USD-converted store audit

{
  "sellerId": "3628678",
  "currency": "USD",
  "sortField": "revenue",
  "sortDirection": "desc"
}

Display Rules

  1. Compact store table — key columns: productId, title, brand, price, monthlySalesUnits, monthlySalesRevenue, rating, balance, turnoverDays, lostProfit, position.
  2. Revenue share = within this seller query — 0-100%; clarify the base.
  3. Russian titles — preserve; translate on user request.
  4. Currency labeling — if converted, note "已按 USD 换算".
  5. Pagination — for stores with thousands of SKUs, suggest tighter filters before paging deep.
  6. No buying advice — the skill shows the store's book, not whether their SKUs are worth copying.

Important Limitations

  • Numeric seller ID only — passing a seller name will not resolve; go through mpstats-ozon-product-search first.
  • Page cap — max 100 rows per page.
  • T-1 dataendDate cannot be today or a future date.
  • No business advice — data-only.
  • Ozon-only — Wildberries / other Russian marketplaces are separate.

User Expression & Scenario Quick Reference

Applicable — Seller-scoped Ozon product metrics:

User Says Scenario
"Show me everything seller 3628678 sells, by sales" Store SKU map
"What are this Ozon store's top revenue products" Store bestseller drill
"How many SKUs does the store have with turnover <20 days" Operational health filter
"Where is this store losing money to stockouts" Lost-profit scan
"Compare two Ozon stores' SKU counts and sales" Store-vs-store benchmarking (call twice)

Not applicable — Needs beyond seller drill-down:

  • Only seller name known → use mpstats-ozon-product-search to resolve the ID
  • Brand-scoped drill → mpstats-ozon-brand-products
  • Category-scoped drill → mpstats-ozon-category-products
  • Single-SKU time-series → mpstats-ozon-product-trend
  • Wildberries / other Russian marketplaces → not covered

Boundary judgment: Use this skill when the dimension is a specific seller and you want the per-SKU table under that shop. For "who are the top sellers in category X" you'd use category drill-down and group by seller client-side.

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_seller_products.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.


For more high-quality, professional cross-border e-commerce skills, set LinkFox Skills.

Install via CLI
npx skills add https://github.com/linkfox-ai/linkfox-skills --skill linkfox-mpstats-ozon-seller-products
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