Ecommerce.Ozon Product Detail logo

Ecommerce.Ozon Product Detail

Organization
nexscope-ai
ecommerce.ozon-product-detail

Nexscope Ozon Russia SKU full detail query for one product ID per call, returning price, discount, Ozon Card price, rating, review count, stock, sales, revenue, revenue potential/lost revenue, listing date, images, and the complete product card. Trigger for Ozon product or SKU detail, price/rating/sales/stock checks, competitor Ozon cards, Nexscope Ozon detail, or Russian marketplace product detail by a known SKU.

Overview

Publishernexscope-ai
Repositorynexscope-ecommerce-skills
Skill nameecommerce.ozon-product-detail
Stars
104
Forks
14
Bundled files
3
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by nexscope-ai on GitHub. Read the source before you install it.

Installation

Install the Ecommerce.Ozon Product Detail AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nexscope-ai/nexscope-ecommerce-skills/tree/main/ecommerce-ozon-product-detail
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nexscope-ai/nexscope-ecommerce-skills.git /tmp/nexscope-ecommerce-skills
mkdir -p .claude/skills
cp -r /tmp/nexscope-ecommerce-skills/ecommerce-ozon-product-detail .claude/skills/ecommerce.ozon-product-detail
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ecommerce.Ozon Product Detail in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ecommerce.Ozon Product Detail on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ecommerce.Ozon Product Detail is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Nexscope Ozon Product Detail

This skill fetches the full product card for one Ozon (Russia) SKU per call via Nexscope. 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

Single-SKU constraint: productId is a single Ozon product ID (integer or string). The former productIds array is deprecated and rejected. When several SKUs are requested, call the tool once per SKU and inform the user that each call consumes credits.

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 requested SKU.

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

ParameterTypeRequiredDescription
productIdinteger|stringyesOne Ozon SKU ID, for example 1786874757
startDatestringnoStats window start, YYYY-MM-DD; latest = yesterday
endDatestringnoStats window end, YYYY-MM-DD; latest = yesterday
includeFbsbooleannotrue to include FBS data; false = FBO-only

Calling the Tool

  • API Endpoint: /mpstats/ozon/productDetail (full parameters/responses/error codes in references/api.md)
  • Python Script: python scripts/ozon_product_detail.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-<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. Single-SKU detail

json
{"productId": 1786874757}

2. Single-SKU lookup with period

json
{
  "productId": 1786874757,
  "startDate": "2025-03-01",
  "endDate": "2025-03-31",
  "includeFbs": true
}

3. FBO-only snapshot

json
{"productId": 1786874757, "includeFbs": false}

4. SKUs discovered upstream — full card

json
{"productId": <one productId from ecommerce.ozon-product-search>}

How to Chain with Other Ozon Skills

  1. Search → detail: Use ecommerce.ozon-product-search to resolve a keyword / brand / seller into productIds, then query selected IDs here one at a time.
  2. Detail vs trend: This endpoint is a period aggregate per SKU; for day-by-day time-series on a single SKU, use ecommerce.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. Failure details — the response may carry successCount / failedCount / failures; when the SKU fails, report its reason rather than silently dropping it.
  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 SKU's deliveryScheme value over assuming FBO.
  7. No business advice — present data; do not extrapolate "this SKU is worth selling" without a wider analysis.

Important Limitations

  • One SKU per call — Send one productId per request. Never send an array or the deprecated productIds field.
  • 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:

User SaysScenario
"Pull Ozon details for these SKUs"Query each selected SKU in a separate, user-approved paid call
"What's the price / rating / stock of Ozon SKU 1786874757"Single-SKU card
"Competitor's Ozon listings, give me sales & rating"Competitor card audit
"Compare FBO vs FBO+FBS metrics for this SKU set"Fulfillment-model comparison

Not applicable — Needs beyond per-SKU card:

  • Keyword-based discovery → use ecommerce.ozon-product-search
  • Day-by-day time-series for one SKU → use ecommerce.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 and wants sales / price / stock / rating, this is the skill. For a list, process one SKU per call without silently multiplying paid requests. If they don't yet have SKUs, route through the search or drill-down skills first.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ecommerce.Ozon Product Detail AI skill do?

Nexscope Ozon Russia SKU full detail query for one product ID per call, returning price, discount, Ozon Card price, rating, review count, stock, sales, revenue, revenue potential/lost revenue, listing date, images, and the complete product card. Trigger for Ozon product or SKU detail, price/rating/sales/stock checks, competitor Ozon cards, Nexscope Ozon detail, or Russian marketplace product detail by a known SKU.

Why use Ecommerce.Ozon Product Detail on TypingMind?

Because you install it once and use it with any model. Ecommerce.Ozon Product Detail is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ecommerce.Ozon Product Detail in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nexscope-ai/nexscope-ecommerce-skills/tree/main/ecommerce-ozon-product-detail. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ecommerce.Ozon Product Detail?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ecommerce.Ozon Product Detail?

As many as you like. As long as a model supports skills, you can use Ecommerce.Ozon Product Detail with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ecommerce.Ozon Product Detail AI skill free?

It is published on GitHub by nexscope-ai. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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