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Политика конфиденциальностиСогласие на обработку ПДн|ИНН 623412173261
    Ozon: рыночные ключевые слова — Скилл для ИИ-агентов | AI Рассвет
    Маркетплейс/Скилл/Ozon: рыночные ключевые слова
    Скилл

    Ozon: рыночные ключевые слова

    Seerfar Ozon market hot keyword search: filters Ozon (and Wildberries) market keywords by multi dimensional metrics including search volume, growth, product count, seller count, competitor count, p...

    Скиллы для маркетинга#GitHub#Ozon#nexscope-ai/nexscope-ecommerce-skills
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    Установить скилл

    Добавьте инструмент одной командой или скачайте проверенный архив версии.

    npx skills add nexscope-ai/nexscope-ecommerce-skills --skill ecommerce-ozon-market-keyword-search
    Скачать ZIP
    Версия
    1.0.0+7fb4686e62c4
    Автор
    Владимир Ломтев
    Исходный код

    Как установить

    1. 1Скопируйте команду из блока установки.
    2. 2Запустите её в терминале из каталога проекта.

    Документация

    Seerfar Ozon Market Keyword Search

    This skill searches Ozon marketplace keywords in the Seerfar analytics database and filters them by rich performance metrics — search volume, 30-day growth, product/seller/competitor counts, average price, monthly sales/revenue, conversion & view concentration, ratings/reviews, and more. Each returned keyword carries a full market profile (market space, return/cancellation rate, top products, Chinese translation), making it the starting point for Ozon keyword selection, blue-ocean term mining, and market-opportunity analysis.

    Core Concepts

    Unit of data is the keyword, not the SKU: unlike a product search, this endpoint returns marketplace search terms ("hot keywords"), each enriched with market metrics. You discover which search terms are worth targeting on Ozon.

    Platform coverage: each keyword record carries a platform field (0 = Ozon, 1 = Wildberries). The dataset is Ozon-centric; Wildberries rows appear where available. There is no input to restrict the platform — filter client-side if needed.

    Date semantics: searchDate selects the data month. Pass 2026-04-01 to get March 2026 data; omit it for the last 30 days. Metrics such as searchVolume (monthly search volume) and count30GrowthRate (monthly search growth) are relative to the selected period.

    Match mode: matchType controls how the keywords array is matched — 0 exact, 1 fuzzy. Choose the mode that fits your discovery intent when filtering by keyword text.

    Parameters

    Parameter Type Required Description
    page object yes Pagination {page, pageSize, orders[]}. page from 1 (default 1), pageSize default 20. orders[] = {field, direction} with direction DESC/ASC.
    keywords array no Keyword list to filter (max 1000); combined with matchType.
    matchType integer no Keyword match mode: 0 exact, 1 fuzzy.
    searchDate string no Data date yyyy-MM-dd; default last 30 days. 2026-04-01 → March 2026 data.
    categories array no Category ID list (max 1000).
    searchVolume {min,max} no Monthly search volume range.
    searchChange30 {min,max} no 30-day search change range.
    monthlySales {min,max} no Monthly sales range.
    monthlyRevenue {min,max} no Monthly revenue range.
    price {min,max} no Average price range.
    productViews {min,max} no Product view range.
    products {min,max} no Product count range.
    volume {min,max} no Volume range.
    marketSpace {min,max} no Market space range.
    conversionSharing {min,max} no Conversion concentration range.
    reviews {min,max} no Review count range.
    ratings {min,max} no Rating range.
    sellers {min,max} no Seller count range.
    weight {min,max} no Weight range.
    uId string no User ID.
    memberId string no Member ID (data attribution).

    All range filters are {min, max} objects; supply either or both bounds. Only page is required.

    Calling the Tool

    • API Endpoint: /seerfar/ozon/marketKeywordSearch (full parameters/responses/error codes in references/api.md)
    • Python Script: python scripts/ozon_market_keyword_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-market-keyword-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. Hottest keywords right now (sort by search volume)

    {"page": {"page": 1, "pageSize": 10, "orders": [{"field": "searchVolume", "direction": "DESC"}]}}
    

    2. Blue-ocean terms — high volume, few sellers

    {"page": {"page": 1, "pageSize": 20, "orders": [{"field": "searchVolume", "direction": "DESC"}]}, "searchVolume": {"min": 10000}, "sellers": {"max": 50}}
    

    3. Filter by keyword text (fuzzy, Russian)

    {"page": {"page": 1, "pageSize": 20}, "keywords": ["телефон"], "matchType": 1}
    

    4. A specific data month with a sales floor

    {"page": {"page": 1, "pageSize": 20}, "searchDate": "2026-04-01", "monthlySales": {"min": 1000}}
    

    How to Build Queries

    1. Lead with page.orders: the dataset is large — always sort by the metric you care about (searchVolume DESC for popularity, count30GrowthRate DESC for rising terms, sellers ASC for low competition).
    2. Stack range filters to find opportunities: combine a high searchVolume floor with a low sellers ceiling to surface blue-ocean keywords; add conversionSharing / marketSpace bounds to qualify demand.
    3. Use keywords + matchType to scope a niche: pass seed terms in Russian with matchType: 1 (fuzzy) to enumerate related long-tail terms.
    4. Pick the right searchDate: omit it for current trends (last 30 days); pass an explicit date for month-over-month comparison.

    Display Rules

    1. Present data only: show keyword metrics in a clear table without subjective advice.
    2. Lead with keyword columns: query / queryCn (Chinese translation), then searchVolume, count30GrowthRate, productCount, sellers, avgPrice.
    3. Russian keywords: preserve the original query; the queryCn field provides a Chinese translation when available.
    4. Platform tag: when both Ozon and Wildberries rows are present, show platform (0/1) so the user can distinguish them.
    5. Large result sets: when total is large, show the top rows and remind the user they can persist the full response via the large-response pattern below, or page further with page.page.
    6. Error handling: when code is not 200 (or errcode is not 200), explain the reason from msg / errmsg and suggest adjusting filters.

    Important Limitations

    • page is required: a payload without page is rejected.
    • No platform selector: the Ozon/Wildberries mix is controlled server-side; filter client-side via the platform field.
    • Category IDs are opaque: categories requires Seerfar category IDs, not human-readable names.
    • Pagination caps: use pageSize and page to page; very large pageSize values may be capped server-side.
    • Nested fields: products[*] (Top Products) and categoryInfos[*] (category path and cross-border availability flag) are structured and decision-useful — see references/api.md for sub-fields. dimension / columns are opaque or partially populated; relevancy / titleDensity / wordCount are usually absent.

    User Expression & Scenario Quick Reference

    Applicable — Ozon keyword market research:

    User Says Scenario
    "What are the Ozon hot / trending keywords" Hottest keywords by search volume
    "Ozon blue-ocean terms: low competition, high search volume" Blue-ocean term mining (high volume, few sellers)
    "Ozon rising keywords / fast-growing terms" Rising keywords (growth sort)
    "Long-tail keywords around a Russian seed term" Fuzzy keyword expansion
    "Market space / competitor count / seller count for an Ozon keyword" Keyword market profile

    Not applicable — Needs beyond keyword market data:

    • A specific SKU's price/sales/stock → use a product-level Seerfar Ozon data source, not this keyword endpoint.
    • A specific seller's catalog → use a seller/shop-level Seerfar Ozon data source.
    • Category-tree browsing → use a category-level Seerfar Ozon data source.
    • Non-Ozon/Wildberries marketplaces → not covered here.

    Boundary judgment: if the user wants to discover and rank search terms on Ozon by market metrics, start here. If they already have a SKU / seller / category and want entities under it, route to the corresponding Seerfar Ozon data source.

    Требования и возможности

    Источник пакета
    https://github.com/nexscope-ai/nexscope-ecommerce-skills/tree/7fb4686e62c427df9e805651a0fb5e1891950055/ecommerce-ozon-market-keyword-search

    Файлы версии

    ПутьРазмерSHA256
    SKILL.md107101800688db2340d59...
    manifest.json3074396b690d2fb1fb3...
    references/api.md88419761a82ac9080af5...
    scripts/ozon_market_keyword_search.py677139153aad69354b42...

    Частые вопросы

    Как установить Ozon: рыночные ключевые слова?
    Используйте команду npx skills add nexscope-ai/nexscope-ecommerce-skills --skill ecommerce-ozon-market-keyword-search или скачайте ZIP-архив.
    Можно ли скачать Ozon: рыночные ключевые слова бесплатно?
    Да, опубликованную версию можно скачать из маркетплейса бесплатно.

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    Установить скилл

    Добавьте инструмент одной командой или скачайте проверенный архив версии.

    npx skills add nexscope-ai/nexscope-ecommerce-skills --skill ecommerce-ozon-market-keyword-search
    Скачать ZIP
    Версия
    1.0.0+7fb4686e62c4
    Автор
    Владимир Ломтев
    Исходный код