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Skillslinkfox-kalodata-tiktok-product

linkfox-kalodata-tiktok-product

Data & analytics

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Updated 10-16 00:00

About this skill

Kalodata - TikTok Product Search & Detail

This skill supports a two-step TikTok Shop product workflow via the Kalodata data source:

  1. Browse TikTok Shop product leaderboards to discover top-ranked and best-selling products.
  2. Fetch one product's full detail by productId.

Use the ranking endpoint when the user wants best-seller rankings, hot products, or product discovery. Use the detail endpoint when the user already has a productId or has selected one product from a ranking result.

Core Concepts

The product ranking endpoint returns a paginated leaderboard filtered by region, dateRange, currency, language, and optional sortField. Each product row includes identity, price, sales volume, revenue (split across video, live, and showcase channels), revenue growth rate, commission rate, and launch date. Results are paginated with pageNumber (1-5) and pageSize (5-100).

The product detail endpoint fetches one TikTok Shop product by productId. It returns the product's price range, sales, revenue (with channel split), commission rate, launch date, review count, category hierarchy, owning shop, and associated video/live/creator counts. The productId usually comes from the ranking response field product_id.

Both endpoints may reflect a statistical delay (T+1). See references/api.md for full request and response details.

Data Fields

Ranking rows include:

Field Description
product_id Product unique ID; pass this as productId for detail lookup
product_name Product title
unit_price Price per unit (currency follows region, e.g. USD for US)
sales_volumn Units sold (field is spelled volumn)
revenue Total revenue / GMV; equals video + live + showcase revenue
video_revenue Revenue from the video channel
live_revenue Revenue from the live-stream channel
showcase_revenue Revenue from the showcase / 橱窗 channel
revenue_growth_rate Revenue growth rate (%)
commission_rate Commission rate as a direct percentage (25.0 = 25%)
launch_date Product launch date (YYYY-MM-DD)

Detail rows additionally include:

Field Description
product_region Product market region (e.g. us)
product_shop_id ID of the shop this product belongs to
pri_cate_id / sec_cate_id / ter_cate_id Primary / secondary / tertiary category IDs
min_price / max_price Minimum / maximum price in the requested currency
product_review_count Number of product reviews
delivery_type Delivery type (e.g. local)
video_number / live_number / creator_number Associated video / live / creator counts
shopping_mall_revenue Revenue from the shopping mall (商城) channel

Detail revenue channel split: revenue = video_revenue + live_revenue + shopping_mall_revenue.

Parameter Guide

Product ranking (/kalodata/product/rank)

Parameter Type Required Description
region string No TikTok Shop market region code, e.g. US. Default US when unspecified
dateRange string No Relative time window, e.g. last7Day, last30Day
currency string No Currency for monetary metrics, e.g. USD
language string No Response language, e.g. zh-CN, en-US
category_ids array No Category ID list filter
shop_id string No Shop ID filter
creator_id string No Creator ID filter
video_id string No Return products associated with the specified video
livestream_id string No Return products associated with the specified livestream
revenue_range string No Revenue / GMV range filter
is_affiliate string No Affiliate filter: PUBLIC_PLAN or NON_AFFILIATE
commission_rate number No Affiliate commission rate, e.g. 0.15
is_tts_product integer No Fully managed product filter: 1 or 0
unit_price_range string No Product unit-price range filter
sortField object No Sorting specification; omit for default ranking
pageNumber integer No Page number, 1-5
pageSize integer No Page size, 5-100

Product detail (/kalodata/product/detail)

Parameter Type Required Description
productId string Yes TikTok product ID from ranking field product_id (string to preserve precision)
region string No Market region code, e.g. US
dateRange string No Time window, e.g. last7Day, last30Day
language string No Response language, e.g. zh-CN, en-US
currency string No Currency for monetary metrics, e.g. USD

How to Call

  • API Endpoint：POST /kalodata/product/rank or POST /kalodata/product/detail(for full parameters/responses/error codes see references/api.md）
  • Python Script：python scripts/kalodata_product_search.py '<JSON 参数>' [--inline] or python scripts/kalodata_product_detail.py '<JSON 参数>' [--inline]
  • Cost Constraints: This tool consumes compute credits; by default, the same parameter combination in the same session is called only once, and the script has a 24h local cache. On failure/empty results, do not automatically switch keywords, paginate, or change the zip code to probe continuously; if further retrieval is needed, first explain to the user that additional consumption will be incurred.

Output Strategy (Script Default Behavior)：

  • Alwayswrite the full response to <cwd>/linkfox/<YYYY-MM-DD>/<session>/data/linkfox-kalodata-tiktok-product-<timestamp>.json（<cwd> is the working directory when the script runs, which in Claude Code is the current project directory;<session> is taken from the environment variable SESSION_ID, automatically aggregated according to the user's task;Writing to /tmp is prohibited, and an error is reported if the current directory is not writable)
  • Response body ≤ 8 KB: after saving to disk, print the full JSON to stdout
  • Response body > 8 KB: after saving to disk, stdout outputs only a summary (top-level fields, common counts such as total/costToken, the length of the largest list field + the first 3 samples)
  • Add --inline to force full printing to stdout (also saved to disk)

Data Reading Recommendations: First look at the summary to determine whether it is sufficient; when specific fields are needed, prefer using jqorConvertFrom-Json to extract on demand from the saved json file, avoiding bringing the entire JSON into context.

Resolving Authentication and Compute Credit Issues

When the following abnormal situations occur, use references/onboarding.md to guide resolution:

Abnormal Situations

  • API Key not configured: The environment variable is not configured LINKFOX_AGENT_API_KEY, and LINKFOXAGENT_API_KEY。
  • Response 401 or 402 status code
  • Response indicates insufficient compute credits or balance: The message contains "insufficient compute credits/insufficient billing/insufficient balance/quota exceeded/insufficient balance/package expired/recharge required/please recharge", or content with a similar meaning.

Usage Examples

1. Browse top TikTok products in the US (last 7 days)

{"region":"US","dateRange":"last7Day","pageSize":20,"pageNumber":1,"currency":"USD"}

2. Fetch one product's detail

{"productId":"1729508370969629931","region":"US","dateRange":"last7Day","currency":"USD"}

3. Discovery-to-detail workflow

Run kalodata_product_search.py first, choose a row's product_id, then pass that value as productId to kalodata_product_detail.py.

Display Rules

  1. Present ranking results in a table with product name, product ID, price, sales volume, revenue (with channel split), growth rate, commission rate, and launch date.
  2. Present detail results as one grouped profile: identity, price range, sales, revenue (channel split), commission, category hierarchy, owning shop, and associated video/live/creator counts.
  3. Always label dateRange, region, and currency when showing monetary metrics.
  4. Use the exact field name sales_volumn.
  5. commission_rate is a direct percentage (25.0 = 25%), not basis points — show with a % sign.
  6. revenue_growth_rate is a percentage — show with a % sign.
  7. Revenue channel split: ranking revenue = video_revenue + live_revenue + showcase_revenue; detail revenue = video_revenue + live_revenue + shopping_mall_revenue. Present the split when useful.
  8. Preserve ranking order unless the user explicitly requests a supported sortField.

Important Limitations

  • Ranking is not keyword search; it browses leaderboards by region and time window.
  • Detail requires productId; it cannot find a product by name alone. Obtain productId from the ranking product_id first.
  • The ranking response does not include total or page count; result count is data.length.
  • pageNumber is limited to 1-5 and pageSize is limited to 5-100.
  • A valid-but-empty request (e.g. an unsupported region) may return errcode 200 with no data field and still be billed.
  • Transient upstream errors may appear as errcode 501 with a Kalodata HTTP 5xx message (e.g. 522/554). Retry the same parameters once or twice; do not change parameters automatically.
  • Use the matching Kalodata video/creator/shop/livestream skills for non-product entities.

User Expression & Scenario Quick Reference

Applicable -- TikTok product ranking or product detail lookup:

User Says Scenario
"TikTok product rankings", "TikTok product leaderboard" Product ranking lookup
"TikTok best-sellers", "TikTok trending product rankings", "TikTok product selection rankings" Best-seller / hot product ranking
"kalodata product rankings", "kaloda rankings" Direct data source reference
"TikTok product details", "TikTok product information" Single product detail lookup
"product price", "product sales volume" Product price / sales
"kalodata product rank/detail", "product analytics" Direct product detail reference

Not applicable -- Needs beyond TikTok products:

  • TikTok video / creator / shop / livestream rankings or details
  • Keyword-based product search
  • Amazon / Shopify / 1688 product research (use the platform-specific skills)
  • TikTok advertising / ad campaign management or content creation

Compute Credit Consumption Rules

Each call consumes 7.0 compute credits.

Users pay fees due to compute credit consumption. Please fully assess: when this skill needs to be called frequently, or when the user's expectation of compute credit consumption is insufficient, be sure to remind the user and let the user decide whether to continue.

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.

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