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TikTok Intelligence KD: shop/detail API

nexscope_data_kd_shop_detail
Read-only

TikTok Intelligence KD: shop/detail API.

Input Schema

NameRequiredDescriptionDefault
regionNoRegion/market code, such as `US`; maximum length 1000
shopIdYesTikTok store unique ID (string, to avoid loss of large integer precision), such as `7495514739648989419`, usually `shop_id` from the list
currencyNoCurrency unit, such as `USD`; maximum length 1000
languageNoReturn language, such as `zh-CN`, `en-US`; maximum length 1000
dateRangeNoTime range, such as `last7Day`, `last30Day`; maximum length 1000
category_idNoCategory ID, which can further limit the returned category dimensions

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.3/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so safety is covered. The description adds nothing further – no mention of what the response includes, whether a region/currency is required for meaningful results, rate limits, or freshness of the underlying data.

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

Conciseness3/5

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

One short sentence, front-loaded with the namespace and resource, with no filler. It is terse and non-redundant in wording, but the brevity reflects under-specification rather than efficient communication.

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

Completeness2/5

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

For a six-parameter lookup tool with no output schema and only minimal annotations, the description should at minimum explain what a shop-detail record contains and what the optional filters change. Neither is present, leaving the agent to infer everything from the parameter names.

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 description coverage is 100%, so the six parameters (shopId, region, currency, language, dateRange, category_id) are already fully documented in the schema. The description adds no extra meaning such as which combination is meaningful or which fields are optional for a richer response, so the baseline of 3 applies.

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

Purpose2/5

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

The description is essentially a verbatim restatement of the title ('TikTok Intelligence KD: shop/detail API') – an endpoint label rather than a statement of what the tool returns. It signals the resource ('shop') and vendor ('KD') but gives no indication of what data a shop detail response contains, nor how it differs from close siblings such as nexscope_data_kd_shop_rank, nexscope_tiktok_shop_analytics or nexscope_chuhaijiang_tiktok_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 Guidelines2/5

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

There is no when-to-use guidance, no prerequisites, and no mention of alternatives. An agent cannot tell from this text whether to call this tool or the ranked-list or analytics variants when asked about a TikTok shop.

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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