Seerfar Ozon Product Detail Search

This skill fetches the full detail of a single Ozon product by its SKU from the Seerfar analytics database — title, price (₽), rating, reviews, QA count, sales (total + daily average + daily trend), revenue, stock, category rank, brand, seller, fulfillment (FBO/FBS/OZON), weight and listing age. The starting point for single-product deep analysis, competitor product teardown, listing diagnostics and sales-trend tracking.

Core Concepts

Unit of data is a single product, looked up by sku: pass one Ozon SKU, get that product's full detail. This is a product-level view (one SKU), not a shop catalog, keyword or category view.

Where the SKU comes from: sku is the Ozon product SKU — the same sku returned by other Seerfar Ozon tools (shop search, keyword back search, category search, market keyword search). If the user only has a product name, URL or shop, first obtain the sku from one of those listing-level sources, then call this skill for the deep dive.

Sales window: dateRange controls the sales/metrics window — totalSales, dailySales, totalRevenue and salesTrendVOList are computed over this range. Default past_30_days. Options: past_7_days / past_30_days / past_60_days / past_90_days / past_180_days / past_365_days.

Sales & price currency: price is in Russian rubles (₽), indicated by currency. totalSales is units over the window; dailySales is the average units/day; totalRevenue is revenue over the window.

Listing age: upTime is the listing timestamp (ms); upDays / upMonths are the derived age in days / months.

Parameters

Parameter	Type	Required	Description
sku	string	yes	Ozon product SKU (e.g. 175924376). The same sku from other Seerfar Ozon tools.
dateRange	string	no	Sales/metrics window. Default past_30_days. One of: past_7_days, past_30_days, past_60_days, past_90_days, past_180_days, past_365_days.
uId	string	no	User ID.
memberId	string	no	Member ID (data attribution).

Only sku is required.

Calling the Tool

• API Endpoint: /seerfar/ozon/productDetailSearch (full parameters/responses/error codes in references/api.md)
• Python Script: python scripts/ozon_product_detail_search.py '<JSON params>' [--inline]
• Cost constraint: This tool consumes credits. Within the same session and same parameter combination, it defaults to a single call with a 24-hour local cache. Do not automatically retry with different keywords, pagination, or parameters on failure/empty results. Inform the user of additional credit consumption before continuing retrieval.

Output strategy (script default behavior):

• Always write the full response to <cwd>/nexscope/<YYYY-MM-DD>/<session>/data/ecommerce-ozon-product-detail-search-<timestamp>.json (<cwd> is the working directory when the script executes, which in Claude Code is the current project directory; <session> is taken from the SESSION_ID environment variable, automatically grouped by user task; do not write to /tmp; error if the current directory is not writable)
• Response body <= 8 KB: write to disk then print full JSON to stdout
• Response body > 8 KB: write to disk then print only a summary to stdout (top-level fields, common counts like total/costToken, length of the largest list field + first 3 samples)
• Add --inline to force full output to stdout (still writes to disk)

Reading data: Check the summary first to determine if it is sufficient. When specific fields are needed, use jq or ConvertFrom-Json to extract from the saved JSON file as needed, avoiding loading the entire JSON into context.

Authentication & Credits

If you encounter authentication or credit issues:

Error conditions

• API Key not configured: The NEXSCOPE_API_KEY environment variable is not set.
• HTTP 401 or 402 status code
• Insufficient credits/balance: Response message indicates credit balance exhausted, quota exceeded, subscription expired, or recharge required.

Resolution steps

1. Set the NEXSCOPE_API_KEY environment variable with a valid API key.
2. If credits are insufficient, visit https://www.nexscope.ai/pricing?co-from=skillNS to top up your balance.
3. For onboarding and setup guidance, refer to https://www.nexscope.ai/help/skills-external-access?co-from=skillNS

Usage Examples

1. Default 30-day detail for a product

{"sku": "175924376"}

2. Last 7 days (recent momentum)

{"sku": "175924376", "dateRange": "past_7_days"}

3. Last 90 days (quarterly trend)

{"sku": "175924376", "dateRange": "past_90_days"}

4. Full year (lifecycle view)

{"sku": "175924376", "dateRange": "past_365_days"}

How to Build Queries

1. Resolve the SKU first: if the user gives a product name, URL or shop rather than a SKU, obtain the sku from a listing-level Seerfar Ozon source (shop search / keyword back search / category search / market keyword search) before calling this skill.
2. Pick dateRange by intent: short windows (past_7_days / past_30_days) for recent momentum and current stock; long windows (past_90_days / past_180_days / past_365_days) for lifecycle, seasonality and ranking stability.
3. Read aggregates, then trend: start with top-level totalSales / dailySales / totalRevenue / stock / categoryRanks for a snapshot, then drill into salesTrendVOList for the daily series.
4. One SKU per call: this endpoint takes a single sku; to compare products, call once per SKU.

Display Rules

1. Present data only: show the product metrics in a clear layout without subjective advice.
2. Lead with identity + snapshot: title, sku, price (₽), reviewRating (reviewCount reviews, questionsAndAnswers Q&A), then the sales snapshot (totalSales, dailySales, totalRevenue, stock) and the window (startDate–endDate).
3. Category ranks: categoryRanks is a monthly rank history ({date, rank, count}) — it has no category name, so show the category path from categoryInfo (titlePath / cnTitlePath) alongside the rank history.
4. Sales trend: salesTrendVOList is a daily series ({date, sales, revenue, price, stock, reviewCount, reviewRating}) — summarize (peak day, trend direction) rather than dumping every row; offer the persisted file for the full series. Some days may have sales: 0 — treat as no-sales, not missing data.
5. Seller & brand: show sellerName (sellerId — negative means an Ozon platform seller) and brandName (brandId) so the user can trace the seller/brand.
6. Fulfillment: fulfillment is an array (e.g. ["FBO"], or ["OZON"] for platform-sold items); join multiple values with /.
7. Listing age: render upTime as a date (ms timestamp) alongside upDays / upMonths.
8. Conditional fields: weight (physical goods only) and grossMargin are schema-defined but absent for some products (e.g. digital goods / Ozon platform sellers) — show - when missing rather than failing. monthlySalesUnits / monthlySalesRevenue mirror the window's totalSales / totalRevenue and are safe to read directly.
9. Empty result: a non-existent sku returns success with total:0 and empty products — tell the user the SKU may be wrong rather than reporting a system error.
10. Error handling: when code is not "200" (or errcode is not 200), explain from msg / errmsg and suggest fixes (check SKU, retry on rate-limit).

Important Limitations

• sku is required; omitting it returns a parameter error.
• Single-SKU endpoint: returns one product's detail; no batch/list mode. Compare products by calling once per SKU.
• dateRange only affects sales aggregates + trend: product metadata (title, price, rating, brand, seller, weight, fulfillment) is a point-in-time snapshot, not windowed.
• Conditional fields: weight (physical goods only) and grossMargin are schema-defined but not always returned — absent for digital goods / Ozon platform sellers. monthlySalesUnits / monthlySalesRevenue are returned and mirror the window's totalSales / totalRevenue.
• Sales/revenue are Seerfar model estimates over the chosen window, not Ozon-official figures.
• total reflects returned record count (1 when the SKU is found), not a catalog total.

User Expression & Scenario Quick Reference

Applicable — deep-dive on one Ozon product:

User Says	Scenario
"View this Ozon product's detail" / "Data for this SKU"	Single product detail
"How many units did this competitor sell in the last 30 days" / "Average daily sales"	Sales snapshot (totalSales / dailySales)
"Revenue for this product"	Revenue (totalRevenue)
"Stock/inventory level for this product"	Stock check (stock)
"Category ranking for this product"	Category rank (categoryRanks)
"Recent sales trend for this product" / "Which day had the best sales"	Daily sales trend (salesTrendVOList)
"Who sells this / what brand"	Seller + brand (sellerName / brandName)
"How long has this product been listed"	Listing age (upDays / upMonths)

Not applicable — needs beyond one product's detail:

• A shop's full product catalog → use the Seerfar Ozon shop search skill.
• Discovering Ozon keywords → use market keyword search / keyword mining / keyword back search.
• Browsing the category tree → use category search.
• Multiple products' summary at once → call this skill per SKU, or use a listing-level source.

Boundary judgment: if the user already has a specific Ozon SKU (or obtained one from a listing-level source) and wants that product's full metrics — sales, revenue, stock, category rank, trend, brand, seller — start here. If they want to discover products, keywords or shops, route to the corresponding Seerfar Ozon skill first.