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Nexscope Ecommerce Data MCP

TikTok Intelligence KD: video/detail API

nexscope_data_kd_video_detail

TikTok Intelligence KD: video/detail API.

Input Schema

NameRequiredDescriptionDefault
regionNoRegion/market code, such as `US`
videoIdYesTikTok video ID such as `7659161409279806734`, usually `video_id` from the list
currencyNoCurrency unit, such as `USD`
languageNoReturn language, for example `zh-CN`, `en-US`
dateRangeNoTime range, such as `last7Day`, `last30Day`

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.1/5.0
Behavior2/5

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

The annotations already declare readOnlyHint=false and openWorldHint=true, so the agent knows this is an external, non-pure-read call. The description adds no behavioral context whatsoever — nothing about auth, rate limits, or why a detail lookup is flagged non-readOnly, which is exactly the kind of nuance this description should surface.

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?

One short sentence with no wasted words but also no substance — this is under-specification rather than effective conciseness. There is nothing front-loaded because there is nothing to load.

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?

With no output schema, the description is the only place an agent could learn what data a video-detail call returns, and it says nothing. For a five-parameter data-fetch tool with an open-world, non-readOnly annotation profile, this is inadequate.

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% with five well-annotated parameters (videoId format example, region, currency, language, dateRange), so the schema does the heavy lifting. The description contributes nothing beyond that, making the baseline 3 appropriate rather than higher.

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?

"TikTok Intelligence KD: video/detail API" restates the title and name rather than describing an action. Only the words "video/detail" hint that it returns per-video data, and nothing distinguishes it from siblings like nexscope_data_kd_video_rank or nexscope_tiktok_video_analytics.

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?

The description gives no when-to-use guidance, prerequisites, or alternative routing. An agent cannot tell from this text whether this is the right tool for a TikTok video lookup versus the many other video tools in the catalog (nexscope_chuhaijiang_tiktok_video_detail, nexscope_tiktok_video_search, etc.).

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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