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Tiktok Shop Analytics

nexscope_tiktok_shop_analytics
Read-only

Search TikTok e-commerce store leaderboards via Kalodata and query detailed information for specific stores. Supports viewing high-ranking, high-sales TikTok Shop stores by region, currency, language, and date range, and using shopId to retrieve revenue, sales volume, on-sale product count, self-operated/affiliate/shopping mall channel revenue, and creator collaboration count. Trigger when users mention TikTok store ranking, TikTok shop leaderboard, TikTok top shops, TikTok store ranking, TikTok Shop store ranking, kalodata store search, kalodata store ranking, TikTok store detail, TikTok shop profile, store revenue, store sales, TikTok shop ranking, TikTok shop leaderboard, TikTok top shops, TikTok store ranking, TikTok shop detail, TikTok store detail, kalodata shop search/detail. Even if the user does not explicitly mention "kalodata", trigger this skill whenever their need involves viewing TikTok store leaderboards or detailed data for a specific TikTok store.

Input Schema

NameRequiredDescriptionDefault
regionNoRegion/market code, e.g., US. Max length 1000
shopIdNoTikTok shop unique ID (string, to avoid large integer precision loss), e.g., 7495514739648989419. Obtainable from the shop_id field in the shop rank response
currencyNoCurrency unit, e.g., USD. Max length 1000
languageNoReturn language, e.g., zh-CN, en-US. Max length 1000
pageSizeNoItems per page, value range 5-100
dateRangeNoTime range, e.g., last7Day (last 7 days), last30Day (last 30 days). Max length 1000
shop_typeNoShop type filter: BRAND or RETAILER
sortFieldNoSort criteria; pass an empty object {} for default rank order when not sorting
pageNumberNoPage number, value range 1-5 (out of range returns errcode 501)
category_idNoOptional category ID dimension
category_idsNoCategory ID list filter; results use the selected category dimension
revenue_rangeNoRevenue / GMV range filter

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare this to be a read-only, non-destructive, open-world tool, so the safety profile is covered. The description adds useful context about what detail data can be retrieved (revenue, sales volume, channel revenue, creator collaboration count) but does not disclose rate limits, authentication needs, pagination behavior, or other operational traits beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose is front-loaded in the first two sentences, but the description is padded with a long, highly repetitive trigger-keyword list that duplicates phrases like 'TikTok shop ranking,' 'TikTok shop leaderboard,' and 'TikTok top shops.' This keyword stuffing reduces clarity and fails the conciseness standard.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 12 optional parameters, two distinct usage modes, and no output schema, so the description should do more to explain mode selection and return values. It partially covers what the detail mode returns and how shopId is used, but does not describe leaderboard output fields or clarify how to invoke each mode cleanly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the input schema already documents all 12 parameters thoroughly. The description adds some mode-level meaning by mentioning region, currency, language, dateRange, and shopId, but does not explain many other parameters such as sortField, pageSize, pageNumber, shop_type, category filters, or revenue_range.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states two specific capabilities: searching TikTok Shop store leaderboards and querying detailed store information via shopId. It names the resource and the data source (Kalodata), though it does not explicitly differentiate this tool from sibling tools such as nexscope_data_kd_shop_rank or nexscope_data_kd_shop_detail.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides extensive trigger phrases indicating when the tool should be invoked, including when 'kalodata' is not mentioned. However, it does not state when to avoid this tool or how to choose between this umbrella tool and more specific sibling tools like nexscope_data_kd_shop_rank and nexscope_data_kd_shop_detail.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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