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Nexscope Ecommerce Data MCP

TikTok Intelligence KD: shop/detail API

nexscope_data_kd_shop_detail

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

D1.7/5.0
Behavior1/5

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

Annotations declare readOnlyHint=false and openWorldHint=true, implying a non-trivial, externally-dependent call, but the description says nothing about cost, rate limits, permissions, or what the request actually hits. The full behavioral burden is unmet.

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?

It is short, but short because it contains essentially no information beyond the tool name. Nothing is front-loaded because there is nothing to front-load; the single sentence carries no content for an agent to act on.

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

Completeness1/5

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

For a 6-parameter, open-world, non-read-only query tool with no output schema, the description should at minimum explain the returned entity and its intended use. It supplies none of that, leaving the agent to infer everything from 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% and every one of the six parameters (region, shopId, currency, language, dateRange, category_id) is documented in the schema with examples, so the description needn't duplicate it. Baseline 3 applies, with no added value from the description.

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 only restates the title: "TikTok Intelligence KD: shop/detail API." It does not say what a 'shop detail' lookup returns or how it differs from the numerous sibling tools (nexscope_chuhaijiang_tiktok_shop_detail, nexscope_tiktok_shop_analytics, nexscope_data_kd_shop_rank). Tautology-level clarity.

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

Usage Guidelines1/5

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

There is no statement of when to use this tool, when not to, or which alternative to pick. With over a dozen near-identical shop/TikTok detail siblings available, the agent gets no routing help at all.

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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